Alternatives to BigLake

Compare BigLake alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to BigLake in 2026. Compare features, ratings, user reviews, pricing, and more from BigLake competitors and alternatives in order to make an informed decision for your business.

  • 1
    KrakenD

    KrakenD

    KrakenD

    KrakenD is a high-performance API Gateway optimized for resource efficiency, capable of managing 70,000 requests per second on a single instance. The stateless architecture allows for straightforward, linear scalability, eliminating the need for complex coordination or database maintenance. It supports various protocols and API specifications, with features like fine-grained access controls, data transformation, and caching. Unique to KrakenD is its ability to aggregate multiple API responses into one, streamlining client-side operations. Security-wise, KrakenD aligns with OWASP standards and doesn't store data, making compliance simpler. It offers a declarative configuration and integrates with third-party logging and metrics tools. With transparent pricing and an open-source option, KrakenD is a comprehensive API Gateway solution for organizations prioritizing performance and scalability.
    Leader badge
    Compare vs. BigLake View Software
    Visit Website
  • 2
    Amazon Redshift
    More customers pick Amazon Redshift than any other cloud data warehouse. Redshift powers analytical workloads for Fortune 500 companies, startups, and everything in between. Companies like Lyft have grown with Redshift from startups to multi-billion dollar enterprises. No other data warehouse makes it as easy to gain new insights from all your data. With Redshift you can query petabytes of structured and semi-structured data across your data warehouse, operational database, and your data lake using standard SQL. Redshift lets you easily save the results of your queries back to your S3 data lake using open formats like Apache Parquet to further analyze from other analytics services like Amazon EMR, Amazon Athena, and Amazon SageMaker. Redshift is the world’s fastest cloud data warehouse and gets faster every year. For performance intensive workloads you can use the new RA3 instances to get up to 3x the performance of any cloud data warehouse.
    Starting Price: $0.25 per hour
  • 3
    AWS Lake Formation
    AWS Lake Formation is a service that makes it easy to set up a secure data lake in days. A data lake is a centralized, curated, and secured repository that stores all your data, both in its original form and prepared for analysis. A data lake lets you break down data silos and combine different types of analytics to gain insights and guide better business decisions. Setting up and managing data lakes today involves a lot of manual, complicated, and time-consuming tasks. This work includes loading data from diverse sources, monitoring those data flows, setting up partitions, turning on encryption and managing keys, defining transformation jobs and monitoring their operation, reorganizing data into a columnar format, deduplicating redundant data, and matching linked records. Once data has been loaded into the data lake, you need to grant fine-grained access to datasets, and audit access over time across a wide range of analytics and machine learning (ML) tools and services.
  • 4
    Delta Lake

    Delta Lake

    Delta Lake

    Delta Lake is an open-source storage layer that brings ACID transactions to Apache Spark™ and big data workloads. Data lakes typically have multiple data pipelines reading and writing data concurrently, and data engineers have to go through a tedious process to ensure data integrity, due to the lack of transactions. Delta Lake brings ACID transactions to your data lakes. It provides serializability, the strongest level of isolation level. Learn more at Diving into Delta Lake: Unpacking the Transaction Log. In big data, even the metadata itself can be "big data". Delta Lake treats metadata just like data, leveraging Spark's distributed processing power to handle all its metadata. As a result, Delta Lake can handle petabyte-scale tables with billions of partitions and files at ease. Delta Lake provides snapshots of data enabling developers to access and revert to earlier versions of data for audits, rollbacks or to reproduce experiments.
  • 5
    Onehouse

    Onehouse

    Onehouse

    The only fully managed cloud data lakehouse designed to ingest from all your data sources in minutes and support all your query engines at scale, for a fraction of the cost. Ingest from databases and event streams at TB-scale in near real-time, with the simplicity of fully managed pipelines. Query your data with any engine, and support all your use cases including BI, real-time analytics, and AI/ML. Cut your costs by 50% or more compared to cloud data warehouses and ETL tools with simple usage-based pricing. Deploy in minutes without engineering overhead with a fully managed, highly optimized cloud service. Unify your data in a single source of truth and eliminate the need to copy data across data warehouses and lakes. Use the right table format for the job, with omnidirectional interoperability between Apache Hudi, Apache Iceberg, and Delta Lake. Quickly configure managed pipelines for database CDC and streaming ingestion.
  • 6
    Tabular

    Tabular

    Tabular

    Tabular is an open table store from the creators of Apache Iceberg. Connect multiple computing engines and frameworks. Decrease query time and storage costs by up to 50%. Centralize enforcement of data access (RBAC) policies. Connect any query engine or framework, including Athena, BigQuery, Redshift, Snowflake, Databricks, Trino, Spark, and Python. Smart compaction, clustering, and other automated data services reduce storage costs and query times by up to 50%. Unify data access at the database or table. RBAC controls are simple to manage, consistently enforced, and easy to audit. Centralize your security down to the table. Tabular is easy to use plus it features high-powered ingestion, performance, and RBAC under the hood. Tabular gives you the flexibility to work with multiple “best of breed” compute engines based on their strengths. Assign privileges at the data warehouse database, table, or column level.
    Starting Price: $100 per month
  • 7
    SelectDB

    SelectDB

    SelectDB

    SelectDB is a modern data warehouse based on Apache Doris, which supports rapid query analysis on large-scale real-time data. From Clickhouse to Apache Doris, to achieve the separation of the lake warehouse and upgrade to the lake warehouse. The fast-hand OLAP system carries nearly 1 billion query requests every day to provide data services for multiple scenes. Due to the problems of storage redundancy, resource seizure, complicated governance, and difficulty in querying and adjustment, the original lake warehouse separation architecture was decided to introduce Apache Doris lake warehouse, combined with Doris's materialized view rewriting ability and automated services, to achieve high-performance data query and flexible data governance. Write real-time data in seconds, and synchronize flow data from databases and data streams. Data storage engine for real-time update, real-time addition, and real-time pre-polymerization.
    Starting Price: $0.22 per hour
  • 8
    Aserto

    Aserto

    Aserto

    Aserto helps developers build secure applications. It makes it easy to add fine-grained, policy-based, real-time access control to your applications and APIs.
 Aserto handles all the heavy lifting required to achieve secure, scalable, high-performance access management. It offers blazing-fast authorization of a local library coupled with a centralized control plane for managing policies, user attributes, relationship data, and decision logs. And it comes with everything you need to implement RBAC or fine-grained authorization models, such as ABAC, and ReBAC. Take a look at our open-source projects: - Topaz.sh: a standalone authorizer you can deploy in your environment to add fine-grained access control to your applications. Topaz lets you combine OPA policies with Zanzibar’s data model for complete flexibility. - OpenPolicyContainers.com (OPCR) secures OPA policies across the lifecycle by adding the ability to tag, ver
  • 9
    lakeFS

    lakeFS

    Treeverse

    lakeFS enables you to manage your data lake the way you manage your code. Run parallel pipelines for experimentation and CI/CD for your data. Simplifying the lives of engineers, data scientists and analysts who are transforming the world with data. lakeFS is an open source platform that delivers resilience and manageability to object-storage based data lakes. With lakeFS you can build repeatable, atomic and versioned data lake operations, from complex ETL jobs to data science and analytics. lakeFS supports AWS S3, Azure Blob Storage and Google Cloud Storage (GCS) as its underlying storage service. It is API compatible with S3 and works seamlessly with all modern data frameworks such as Spark, Hive, AWS Athena, Presto, etc. lakeFS provides a Git-like branching and committing model that scales to exabytes of data by utilizing S3, GCS, or Azure Blob for storage.
  • 10
    Tokern

    Tokern

    Tokern

    Open source data governance suite for databases and data lakes. Tokern is a simple to use toolkit to collect, organize and analyze data lake's metadata. Run as a command-line app for quick tasks. Run as a service for continuous collection of metadata. Analyze lineage, access control and PII datasets using reporting dashboards or programmatically in Jupyter notebooks. Tokern is an open source data governance suite for databases and data lakes. Improve ROI of your data, comply with regulations like HIPAA, CCPA and GDPR and protect critical data from insider threats with confidence. Centralized metadata management of users, datasets and jobs. Powers other data governance features. Track Column Level Data Lineage for Snowflake, AWS Redshift and BigQuery. Build lineage from query history or ETL scripts. Explore lineage using interactive graphs or programmatically using APIs or SDKs.
  • 11
    Mitzu

    Mitzu

    Mitzu.io

    Mitzu.io is a warehouse-native analytics platform designed for SaaS and e-commerce businesses. It enables teams to derive actionable insights directly from their data warehouses or lakes without complex data modeling or copying data into third-party systems. The platform integrates seamlessly with popular data storage solutions like Snowflake, BigQuery, Redshift, Databricks, and Trino. Mitzu's key feature is its capability to provide self-service analytics. It empowers non-technical users like product managers, marketers, and sales teams to explore data and generate insights without SQL expertise. The platform automatically generates SQL queries based on user interactions, providing real-time analytics for monitoring user behavior, feature usage, and engagement patterns. One of Mitzu's main advantages is that it works directly on raw datasets in the warehouse, eliminating the need for data duplication. Also, it works with seat-based pricing! Cheaper than the alternatives.
    Starting Price: $95 per month
  • 12
    Dataplex Universal Catalog
    Dataplex Universal Catalog is Google Cloud’s intelligent governance platform for data and AI artifacts. It centralizes discovery, management, and monitoring across data lakes, warehouses, and databases, giving teams unified access to trusted data. With Vertex AI integration, users can instantly find datasets, models, features, and related assets in one search experience. It supports semantic search, data lineage, quality checks, and profiling to improve trust and compliance. Integrated with BigQuery and BigLake, it enables end-to-end governance for both proprietary and open lakehouse environments. Dataplex Universal Catalog helps organizations democratize data access, enforce governance, and accelerate analytics and AI initiatives.
    Starting Price: $0.060 per hour
  • 13
    IBM watsonx.data
    Put your data to work, wherever it resides, with the open, hybrid data lakehouse for AI and analytics. Connect your data from anywhere, in any format, and access through a single point of entry with a shared metadata layer. Optimize workloads for price and performance by pairing the right workloads with the right query engine. Embed natural-language semantic search without the need for SQL, so you can unlock generative AI insights faster. Manage and prepare trusted data to improve the relevance and precision of your AI applications. Use all your data, everywhere. With the speed of a data warehouse, the flexibility of a data lake, and special features to support AI, watsonx.data can help you scale AI and analytics across your business. Choose the right engines for your workloads. Flexibly manage cost, performance, and capability with access to multiple open engines including Presto, Presto C++, Spark Milvus, and more.
  • 14
    Google Cloud Data Fusion
    Open core, delivering hybrid and multi-cloud integration. Data Fusion is built using open source project CDAP, and this open core ensures data pipeline portability for users. CDAP’s broad integration with on-premises and public cloud platforms gives Cloud Data Fusion users the ability to break down silos and deliver insights that were previously inaccessible. Integrated with Google’s industry-leading big data tools. Data Fusion’s integration with Google Cloud simplifies data security and ensures data is immediately available for analysis. Whether you’re curating a data lake with Cloud Storage and Dataproc, moving data into BigQuery for data warehousing, or transforming data to land it in a relational store like Cloud Spanner, Cloud Data Fusion’s integration makes development and iteration fast and easy.
  • 15
    VeloDB

    VeloDB

    VeloDB

    Powered by Apache Doris, VeloDB is a modern data warehouse for lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within seconds. Storage engine with real-time upsert、append and pre-aggregation. Unparalleled performance in both real-time data serving and interactive ad-hoc queries. Not just structured but also semi-structured data. Not just real-time analytics but also batch processing. Not just run queries against internal data but also work as a federate query engine to access external data lakes and databases. Distributed design to support linear scalability. Whether on-premise deployment or cloud service, separation or integration of storage and compute, resource usage can be flexibly and efficiently adjusted according to workload requirements. Built on and fully compatible with open source Apache Doris. Support MySQL protocol, functions, and SQL for easy integration with other data tools.
  • 16
    Electrik.Ai

    Electrik.Ai

    Electrik.Ai

    Automatically ingest marketing data into any data warehouse or cloud file storage of your choice such as BigQuery, Snowflake, Redshift, Azure SQL, AWS S3, Azure Data Lake, Google Cloud Storage with our fully managed ETL pipelines in the cloud. Our hosted marketing data warehouse integrates all your marketing data and provides ad insights, cross-channel attribution, content insights, competitor Insights, and more. Our customer data platform performs identity resolution in real-time across data sources thus enabling a unified view of the customer and their journey. Electrik.AI is a cloud-based marketing analytics software and full-service platform. Electrik.AI’s Google Analytics Hit Data Extractor enriches and extracts the un-sampled hit level data sent to Google Analytics from the website or application and periodically ships it to your desired destination database/data warehouse or file/data lake.
    Starting Price: $49 per month
  • 17
    Imply

    Imply

    Imply

    Imply is a real-time analytics platform built on Apache Druid, designed to handle large-scale, high-performance OLAP (Online Analytical Processing) workloads. It offers real-time data ingestion, fast query performance, and the ability to perform complex analytical queries on massive datasets with low latency. Imply is tailored for organizations that need interactive analytics, real-time dashboards, and data-driven decision-making at scale. It provides a user-friendly interface for data exploration, along with advanced features such as multi-tenancy, fine-grained access controls, and operational insights. With its distributed architecture and scalability, Imply is well-suited for use cases in streaming data analytics, business intelligence, and real-time monitoring across industries.
  • 18
    Trino

    Trino

    Trino

    Trino is a query engine that runs at ludicrous speed. Fast-distributed SQL query engine for big data analytics that helps you explore your data universe. Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low-latency analytics. The largest organizations in the world use Trino to query exabyte-scale data lakes and massive data warehouses alike. Supports diverse use cases, ad-hoc analytics at interactive speeds, massive multi-hour batch queries, and high-volume apps that perform sub-second queries. Trino is an ANSI SQL-compliant query engine, that works with BI tools such as R, Tableau, Power BI, Superset, and many others. You can natively query data in Hadoop, S3, Cassandra, MySQL, and many others, without the need for complex, slow, and error-prone processes for copying the data. Access data from multiple systems within a single query.
    Starting Price: Free
  • 19
    SecuPi

    SecuPi

    SecuPi

    SecuPi provides an overarching data-centric security platform, delivering fine-grained access control (ABAC), Database Activity Monitoring (DAM) and de-identification using FPE encryption, physical and dynamic masking and deletion (RTBF). SecuPi offers wide coverage across packaged and home-grown applications, direct access tools, big data, and cloud environments. One data security platform for monitoring, controlling, encrypting, and classifying data across all cloud & on-prem platforms seamlessly with no code changes. Agile and efficient configurable platform to meet current & future regulatory and audit requirements. No source-code changes with fast & cost-efficient implementation. SecuPi’s fine-grain data access controls protect sensitive data so users get access only to data they are entitled to view, and no more. Seamlessly integrate with Starburst/Trino for automated enforcement of data access policies and data protection operations.
  • 20
    Deep Lake

    Deep Lake

    activeloop

    Generative AI may be new, but we've been building for this day for the past 5 years. Deep Lake thus combines the power of both data lakes and vector databases to build and fine-tune enterprise-grade, LLM-based solutions, and iteratively improve them over time. Vector search does not resolve retrieval. To solve it, you need a serverless query for multi-modal data, including embeddings or metadata. Filter, search, & more from the cloud or your laptop. Visualize and understand your data, as well as the embeddings. Track & compare versions over time to improve your data & your model. Competitive businesses are not built on OpenAI APIs. Fine-tune your LLMs on your data. Efficiently stream data from remote storage to the GPUs as models are trained. Deep Lake datasets are visualized right in your browser or Jupyter Notebook. Instantly retrieve different versions of your data, materialize new datasets via queries on the fly, and stream them to PyTorch or TensorFlow.
    Starting Price: $995 per month
  • 21
    Apache Doris

    Apache Doris

    The Apache Software Foundation

    Apache Doris is a modern data warehouse for real-time analytics. It delivers lightning-fast analytics on real-time data at scale. Push-based micro-batch and pull-based streaming data ingestion within a second. Storage engine with real-time upsert, append and pre-aggregation. Optimize for high-concurrency and high-throughput queries with columnar storage engine, MPP architecture, cost based query optimizer, vectorized execution engine. Federated querying of data lakes such as Hive, Iceberg and Hudi, and databases such as MySQL and PostgreSQL. Compound data types such as Array, Map and JSON. Variant data type to support auto data type inference of JSON data. NGram bloomfilter and inverted index for text searches. Distributed design for linear scalability. Workload isolation and tiered storage for efficient resource management. Supports shared-nothing clusters as well as separation of storage and compute.
    Starting Price: Free
  • 22
    VE3 DataWise

    VE3 DataWise

    VE3 Global

    DataWise is a purpose-built solution for SAP data modernization. It bridges SAP (ECC or S/4HANA) and the Databricks Lakehouse to transform siloed operational data into a trusted, analytics-ready foundation for real-time decisions and AI innovation. DataWise accelerates value with SAP-native connectors and prebuilt models for common modules (SD, MM, PM, Finance, Ariba, SuccessFactors). Automated ELT pipelines land data into Delta Lake, while MatchX AI-powered data quality engine performs cleansing, standardization, deduplication, and entity matching to raise data accuracy and completeness at scale. Governance is enforced end-to-end through Unity Catalog, fine-grained access controls, and lineage. Once standardized and governed, DataWise activates your SAP data across BI dashboards, machine-learning features, and event-driven workflows without disrupting core ERP.
  • 23
    Cosmian

    Cosmian

    Cosmian

    Cosmian’s Data Protection Suite delivers a comprehensive, next-generation cryptography platform to secure sensitive data and applications in use, at rest, and in motion across cloud and edge environments. It includes Cosmian Covercrypt, a high-performance hybrid classical and post-quantum encryption library with traceable, fine-grained access control; Cosmian KMS, an open-source, centralized key management system that enables massive client-side encryption on the fly; and Cosmian VM, a plug-and-play, verifiable confidential virtual machine that continuously cryptographically verifies its own integrity without disrupting existing workflows. An AI Runner (“Cosmian AI”) operates within the confidential VM to enable secure model training, querying, and fine-tuning, no coding required. All components integrate via simple APIs and deploy rapidly through AWS, Azure, or Google Cloud marketplaces, empowering organizations to build zero-trust architectures.
  • 24
    TruLens

    TruLens

    TruLens

    TruLens is an open-source Python library designed to systematically evaluate and track Large Language Model (LLM) applications. It provides fine-grained instrumentation, feedback functions, and a user interface to compare and iterate on app versions, facilitating rapid development and improvement of LLM-based applications. Programmatic tools that assess the quality of inputs, outputs, and intermediate results from LLM applications, enabling scalable evaluation. Fine-grained, stack-agnostic instrumentation and comprehensive evaluations help identify failure modes and systematically iterate to improve applications. An easy-to-use interface that allows developers to compare different versions of their applications, facilitating informed decision-making and optimization. TruLens supports various use cases, including question-answering, summarization, retrieval-augmented generation, and agent-based applications.
    Starting Price: Free
  • 25
    Upsolver

    Upsolver

    Upsolver

    Upsolver makes it incredibly simple to build a governed data lake and to manage, integrate and prepare streaming data for analysis. Define pipelines using only SQL on auto-generated schema-on-read. Easy visual IDE to accelerate building pipelines. Add Upserts and Deletes to data lake tables. Blend streaming and large-scale batch data. Automated schema evolution and reprocessing from previous state. Automatic orchestration of pipelines (no DAGs). Fully-managed execution at scale. Strong consistency guarantee over object storage. Near-zero maintenance overhead for analytics-ready data. Built-in hygiene for data lake tables including columnar formats, partitioning, compaction and vacuuming. 100,000 events per second (billions daily) at low cost. Continuous lock-free compaction to avoid “small files” problem. Parquet-based tables for fast queries.
  • 26
    OpenDocMan

    OpenDocMan

    OpenDocMan

    OpenDocMan is a free, web-based, open-source document management system (DMS) written in PHP and designed to comply with ISO 17025 and OIE standards for document management. It features web-based access, fine-grained control of access to files, and automated install and upgrades. OpenDocMan was developed under the open-source GPL license, which in a nutshell allows you to use the program for free and modify it any way you wish. We also encourage feedback from our users when they encounter issues, or have suggestions. Free document management software is good for you. IT staff and managers can delegate document management duties to any number of staff members, through user and group permissions. Permissions can be set as restrictively or permissively as needed.
  • 27
    Dremio

    Dremio

    Dremio

    Dremio delivers lightning-fast queries and a self-service semantic layer directly on your data lake storage. No moving data to proprietary data warehouses, no cubes, no aggregation tables or extracts. Just flexibility and control for data architects, and self-service for data consumers. Dremio technologies like Data Reflections, Columnar Cloud Cache (C3) and Predictive Pipelining work alongside Apache Arrow to make queries on your data lake storage very, very fast. An abstraction layer enables IT to apply security and business meaning, while enabling analysts and data scientists to explore data and derive new virtual datasets. Dremio’s semantic layer is an integrated, searchable catalog that indexes all of your metadata, so business users can easily make sense of your data. Virtual datasets and spaces make up the semantic layer, and are all indexed and searchable.
  • 28
    IBM Cloud SQL Query
    Serverless, interactive querying for analyzing data in IBM Cloud Object Storage. Query your data directly where it is stored, there's no ETL, no databases, and no infrastructure to manage. IBM Cloud SQL Query uses Apache Spark, an open-source, fast, extensible, in-memory data processing engine optimized for low latency and ad hoc analysis of data. No ETL or schema definition needed to enable SQL queries. Analyze data where it sits in IBM Cloud Object Storage using our query editor and REST API. Run as many queries as you need; with pay-per-query pricing, you pay only for the data scan. Compress or partition data to drive savings and performance. IBM Cloud SQL Query is highly available and executes queries using compute resources across multiple facilities. IBM Cloud SQL Query supports a variety of data formats such as CSV, JSON and Parquet, and allows for standard ANSI SQL.
    Starting Price: $5.00/Terabyte-Month
  • 29
    Amazon EMR
    Amazon EMR is the industry-leading cloud big data platform for processing vast amounts of data using open-source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. With EMR you can run Petabyte-scale analysis at less than half of the cost of traditional on-premises solutions and over 3x faster than standard Apache Spark. For short-running jobs, you can spin up and spin down clusters and pay per second for the instances used. For long-running workloads, you can create highly available clusters that automatically scale to meet demand. If you have existing on-premises deployments of open-source tools such as Apache Spark and Apache Hive, you can also run EMR clusters on AWS Outposts. Analyze data using open-source ML frameworks such as Apache Spark MLlib, TensorFlow, and Apache MXNet. Connect to Amazon SageMaker Studio for large-scale model training, analysis, and reporting.
  • 30
    Amazon Security Lake
    Amazon Security Lake automatically centralizes security data from AWS environments, SaaS providers, on-premises, and cloud sources into a purpose-built data lake stored in your account. With Security Lake, you can get a more complete understanding of your security data across your entire organization. You can also improve the protection of your workloads, applications, and data. Security Lake has adopted the Open Cybersecurity Schema Framework (OCSF), an open standard. With OCSF support, the service normalizes and combines security data from AWS and a broad range of enterprise security data sources. Use your preferred analytics tools to analyze your security data while retaining complete control and ownership over that data. Centralize data visibility from cloud and on-premises sources across your accounts and AWS Regions. Streamline your data management at scale by normalizing your security data to an open standard.
    Starting Price: $0.75 per GB per month
  • 31
    Apache Iceberg

    Apache Iceberg

    Apache Software Foundation

    Iceberg is a high-performance format for huge analytic tables. Iceberg brings the reliability and simplicity of SQL tables to big data, while making it possible for engines like Spark, Trino, Flink, Presto, Hive and Impala to safely work with the same tables, at the same time. Iceberg supports flexible SQL commands to merge new data, update existing rows, and perform targeted deletes. Iceberg can eagerly rewrite data files for read performance, or it can use delete deltas for faster updates. Iceberg handles the tedious and error-prone task of producing partition values for rows in a table and skips unnecessary partitions and files automatically. No extra filters are needed for fast queries, and the table layout can be updated as data or queries change.
    Starting Price: Free
  • 32
    Cribl Lake
    Storage that doesn’t lock data in. Get up and running fast with a managed data lake. Easily store, access, and retrieve data, without being a data expert. Cribl Lake keeps you from drowning in data. Easily store, manage, enforce policy on, and access data when you need. Dive into the future with open formats and unified retention, security, and access control policies. Let Cribl handle the heavy lifting so data can be usable and valuable to the teams and tools that need it. Minutes, not months to get up and running with Cribl Lake. Zero configuration with automated provisioning and out-of-the-box integrations. Streamline workflows with Stream and Edge for powerful data ingestion and routing. Cribl Search unifies queries no matter where data is stored, so you can get value from data without delays. Take an easy path to collect and store data for long-term retention. Comply with legal and business requirements for data retention by defining specific retention periods.
  • 33
    Apache Ranger

    Apache Ranger

    The Apache Software Foundation

    Apache Ranger™ is a framework to enable, monitor and manage comprehensive data security across the Hadoop platform. The vision with Ranger is to provide comprehensive security across the Apache Hadoop ecosystem. With the advent of Apache YARN, the Hadoop platform can now support a true data lake architecture. Enterprises can potentially run multiple workloads, in a multi tenant environment. Data security within Hadoop needs to evolve to support multiple use cases for data access, while also providing a framework for central administration of security policies and monitoring of user access. Centralized security administration to manage all security related tasks in a central UI or using REST APIs. Fine grained authorization to do a specific action and/or operation with Hadoop component/tool and managed through a central administration tool. Standardize authorization method across all Hadoop components. Enhanced support for different authorization methods - Role based access control etc.
  • 34
    Lentiq

    Lentiq

    Lentiq

    Lentiq is a collaborative data lake as a service environment that’s built to enable small teams to do big things. Quickly run data science, machine learning and data analysis at scale in the cloud of your choice. With Lentiq, your teams can ingest data in real time and then process, clean and share it. From there, Lentiq makes it possible to build, train and share models internally. Simply put, data teams can collaborate with Lentiq and innovate with no restrictions. Data lakes are storage and processing environments, which provide ML, ETL, schema-on-read querying capabilities and so much more. Are you working on some data science magic? You definitely need a data lake. In the Post-Hadoop era, the big, centralized data lake is a thing of the past. With Lentiq, we use data pools, which are multi-cloud, interconnected mini-data lakes. They work together to give you a stable, secure and fast data science environment.
  • 35
    Qubole

    Qubole

    Qubole

    Qubole is a simple, open, and secure Data Lake Platform for machine learning, streaming, and ad-hoc analytics. Our platform provides end-to-end services that reduce the time and effort required to run Data pipelines, Streaming Analytics, and Machine Learning workloads on any cloud. No other platform offers the openness and data workload flexibility of Qubole while lowering cloud data lake costs by over 50 percent. Qubole delivers faster access to petabytes of secure, reliable and trusted datasets of structured and unstructured data for Analytics and Machine Learning. Users conduct ETL, analytics, and AI/ML workloads efficiently in end-to-end fashion across best-of-breed open source engines, multiple formats, libraries, and languages adapted to data volume, variety, SLAs and organizational policies.
  • 36
    ELCA Smart Data Lake Builder
    Classical Data Lakes are often reduced to basic but cheap raw data storage, neglecting significant aspects like transformation, data quality and security. These topics are left to data scientists, who end up spending up to 80% of their time acquiring, understanding and cleaning data before they can start using their core competencies. In addition, classical Data Lakes are often implemented by separate departments using different standards and tools, which makes it harder to implement comprehensive analytical use cases. Smart Data Lakes solve these various issues by providing architectural and methodical guidelines, together with an efficient tool to build a strong high-quality data foundation. Smart Data Lakes are at the core of any modern analytics platform. Their structure easily integrates prevalent Data Science tools and open source technologies, as well as AI and ML. Their storage is cheap and scalable, supporting both unstructured data and complex data structures.
    Starting Price: Free
  • 37
    Tencent Cloud Message Queue
    CMQ can efficiently send/receive and push tens of millions of messages and retain an unlimited number of messages. It features an extremely high throughput and can process over 100,000 queries per second (QPS) with one single cluster, fully meeting the messaging needs of your businesses. When each message is returned to the user, CMQ writes three copies of the message data to different physical servers so that when one of the servers fails, the backend data replication mechanism can quickly migrate the data. CMQ supports HTTPS-based secure access and utilizes Tencent Cloud's multi-dimensional security protection to defend against network attacks and protect the privacy of your businesses. Plus, it supports managing master/sub-accounts and collaborator accounts for fine-grained resource access control.
  • 38
    Amazon MSK
    Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service that makes it easy for you to build and run applications that use Apache Kafka to process streaming data. Apache Kafka is an open-source platform for building real-time streaming data pipelines and applications. With Amazon MSK, you can use native Apache Kafka APIs to populate data lakes, stream changes to and from databases, and power machine learning and analytics applications. Apache Kafka clusters are challenging to setup, scale, and manage in production. When you run Apache Kafka on your own, you need to provision servers, configure Apache Kafka manually, replace servers when they fail, orchestrate server patches and upgrades, architect the cluster for high availability, ensure data is durably stored and secured, setup monitoring and alarms, and carefully plan scaling events to support load changes.
    Starting Price: $0.0543 per hour
  • 39
    P0 Security

    P0 Security

    P0 Security

    Find and fix vulnerabilities, request and grant privileged access. You should never need to trade off infrastructure security against developer velocity. Process access escalations in minutes. No more tickets, better-scoped permissions, and automatic expiration. P0 Security enables engineers to request just-in-time, fine-grained access to any cloud resource, without becoming an expert in the language of cloud IAM. DevOps teams can automate provisioning and expiry of access, without needing to constantly update static IDP groups. Provide developers just-in-time, short-lived, and fine-grained access to a production stack (AWS, GCP, Kubernetes) for deploying or troubleshooting services. Automate periodic access reviews of your cloud environment, and accelerate compliance for SOC2 and ISO 27001, without overburdening your teams. Provide engineers and customer success teams just-in-time and short-lived access to customer data in a cloud environment, or in a data warehouse.
    Starting Price: $25 per month
  • 40
    Apache PredictionIO
    Apache PredictionIO® is an open-source machine learning server built on top of a state-of-the-art open-source stack for developers and data scientists to create predictive engines for any machine learning task. It lets you quickly build and deploy an engine as a web service on production with customizable templates. Respond to dynamic queries in real-time once deployed as a web service, evaluate and tune multiple engine variants systematically, and unify data from multiple platforms in batch or in real-time for comprehensive predictive analytics. Speed up machine learning modeling with systematic processes and pre-built evaluation measures, support machine learning and data processing libraries such as Spark MLLib and OpenNLP. Implement your own machine learning models and seamlessly incorporate them into your engine. Simplify data infrastructure management. Apache PredictionIO® can be installed as a full machine learning stack, bundled with Apache Spark, MLlib, HBase, Akka HTTP, etc.
    Starting Price: Free
  • 41
    Cloudflare R2

    Cloudflare R2

    Cloudflare

    Cloudflare R2 is a global object storage service that allows developers to store large amounts of unstructured data without the costly egress bandwidth fees associated with typical cloud storage services. It supports multiple scenarios, including storage for cloud-native applications, web content, podcast episodes, data lakes, and outputs for large batch processes such as machine learning model artifacts or datasets. R2 offers features like location hints to optimize data access, CORS configuration for interacting with objects, public buckets to expose contents directly to the Internet, and bucket-scoped tokens for granular access control. It integrates with Cloudflare Workers, enabling developers to perform authentication, route requests, and deploy edge functions across a network of over 330 data centers. Additionally, R2 supports Apache Iceberg through its data catalog, transforming object storage into a fully functional data warehouse without management overhead.
    Starting Price: $0.015 per GB
  • 42
    Perplexity Search API
    Perplexity has launched the Perplexity Search API, giving developers access to the same global-scale indexing and retrieval infrastructure that powers Perplexity’s public answer engine. The API indexes hundreds of billions of webpages and is optimized for the unique demands of AI workflows; it breaks documents into fine-grained subunits so that responses return highly relevant snippets already ranked against the original query, reducing preprocessing and improving downstream performance. To maintain freshness, the index processes tens of thousands of updates every second using an AI-driven content understanding module that dynamically parses web content and iteratively self-improves via real-time query feedback. The API returns rich, structured responses suitable for both AI agents and traditional apps, rather than limited, document-level outputs. Alongside the API, Perplexity is releasing an SDK, an open source evaluation framework, and detailed research into their design.
  • 43
    Amazon Data Firehose
    Easily capture, transform, and load streaming data. Create a delivery stream, select your destination, and start streaming real-time data with just a few clicks. Automatically provision and scale compute, memory, and network resources without ongoing administration. Transform raw streaming data into formats like Apache Parquet, and dynamically partition streaming data without building your own processing pipelines. Amazon Data Firehose provides the easiest way to acquire, transform, and deliver data streams within seconds to data lakes, data warehouses, and analytics services. To use Amazon Data Firehose, you set up a stream with a source, destination, and required transformations. Amazon Data Firehose continuously processes the stream, automatically scales based on the amount of data available, and delivers it within seconds. Select the source for your data stream or write data using the Firehose Direct PUT API.
    Starting Price: $0.075 per month
  • 44
    doolytic

    doolytic

    doolytic

    doolytic is leading the way in big data discovery, the convergence of data discovery, advanced analytics, and big data. doolytic is rallying expert BI users to the revolution in self-service exploration of big data, revealing the data scientist in all of us. doolytic is an enterprise software solution for native discovery on big data. doolytic is based on best-of-breed, scalable, open-source technologies. Lightening performance on billions of records and petabytes of data. Structured, unstructured and real-time data from any source. Sophisticated advanced query capabilities for expert users, Integration with R for advanced and predictive applications. Search, analyze, and visualize data from any format, any source in real-time with the flexibility of Elastic. Leverage the power of Hadoop data lakes with no latency and concurrency issues. doolytic solves common BI problems and enables big data discovery without clumsy and inefficient workarounds.
  • 45
    Permify

    Permify

    Permify

    Permify is an authorization service designed to help developers build and manage fine-grained, scalable access control systems within their applications. Inspired by Google's Zanzibar, Permify enables the structuring of authorization models, storage of authorization data in preferred databases, and interaction with its API to handle authorization queries across various applications and services. It supports multiple access control models, including Role-Based Access Control (RBAC), and Attribute-Based Access Control (ABAC), allowing for the creation of granular permissions and policies. Permify centralized authorization logic, abstracting it from the codebase to facilitate easier reasoning, testing, and debugging. It offers flexible policy storage options and provides a role manager to handle RBAC role hierarchies. The platform also supports filtered policy management for efficient enforcement in large, multi-tenant environments.
    Starting Price: Free
  • 46
    OpenFGA

    OpenFGA

    The Linux Foundation

    OpenFGA is an open source authorization solution that enables developers to implement fine-grained access control using a user-friendly modeling language and APIs. Inspired by Google's Zanzibar paper, it supports various access control models, including Relationship-Based Access Control (ReBAC), Role-Based Access Control (RBAC), and Attribute-Based Access Control (ABAC). OpenFGA offers SDKs for multiple programming languages, such as Java, .NET, JavaScript, Go, and Python, facilitating seamless integration into diverse applications. The platform is designed for high performance, capable of processing authorization checks in milliseconds, making it suitable for projects ranging from small startups to large enterprises. Operating under the Cloud Native Computing Foundation (CNCF) as a sandbox project, OpenFGA emphasizes transparency and community collaboration, inviting contributions to its development and governance.
    Starting Price: Free
  • 47
    Jmix

    Jmix

    Haulmont Technology

    Discover a rapid application development platform that supercharges your digital initiatives without low-code limitations, vendor dependency, and usage-based fees. Jmix general purpose open architecture based on a future-proof technology stack is capable to support various digital initiatives across the organization. Jmix applications are indeed yours and can be supported independently thanks to open-source runtime utilizing mainstream technologies. Your data is secure with a server-side frontend development model and fine-grained access control. Any Java or Kotlin developer is a full-stack Jmix developer - you don’t need separate backend and frontend teams. Visual tools help onboard developers who have little experience or move from an obsolete stack. Jmix’s data-centric approach and single development language make it a natural fit to migrate legacy applications. Jmix supercharges your team with high-productivity tools and ready-to-use components.
    Starting Price: $45 per month
  • 48
    Dylan

    Dylan

    Dylan

    It is dynamic while providing a programming model designed to support efficient machine code generation, including fine-grained control over dynamic and static behaviors. Describes the Open Dylan implementation of the Dylan language, a core set of Dylan libraries, and a library interchange mechanism. The core libraries provide many language extensions, a threads interface, and object finalization, printing and output formatting modules, a streams module, a sockets module, and modules providing an interface to operating system features such as the file system, time and date information, the host machine environment, as well as a foreign function interface and some low-level access to the Microsoft Win32 API.
    Starting Price: Free
  • 49
    Airbyte

    Airbyte

    Airbyte

    Airbyte is an open-source data integration platform designed to help businesses synchronize data from various sources to their data warehouses, lakes, or databases. The platform provides over 550 pre-built connectors and enables users to easily create custom connectors using low-code or no-code tools. Airbyte's solution is optimized for large-scale data movement, enhancing AI workflows by seamlessly integrating unstructured data into vector databases like Pinecone and Weaviate. It offers flexible deployment options, ensuring security, compliance, and governance across all models.
    Starting Price: $2.50 per credit
  • 50
    Cazena

    Cazena

    Cazena

    Cazena’s Instant Data Lake accelerates time to analytics and AI/ML from months to minutes. Powered by its patented automated data platform, Cazena delivers the first SaaS experience for data lakes. Zero operations required. Enterprises need a data lake that easily supports all of their data and tools for analytics, machine learning and AI. To be effective, a data lake must offer secure data ingestion, flexible data storage, access and identity management, tool integration, optimization and more. Cloud data lakes are complicated to do yourself, which is why they require expensive teams. Cazena’s Instant Cloud Data Lakes are instantly production-ready for data loading and analytics. Everything is automated, supported on Cazena’s SaaS Platform with continuous Ops and self-service access via the Cazena SaaS Console. Cazena's Instant Data Lakes are turnkey and production-ready for secure data ingest, storage and analytics.