Best Semantic Layer Tools with a Free Trial

dbt helps data teams transform raw data into trusted, analysis-ready datasets faster. With dbt, data analysts and data engineers can collaborate on version-controlled SQL models, enforce testing and documentation standards, lean on detailed metadata to troubleshoot and optimize pipelines, and deploy transformations reliably at scale. Built on modern software engineering best practices, dbt brings transparency and governance to every step of the data transformation workflow. Thousands of companies, from startups to Fortune 500 enterprises, rely on dbt to improve data quality and trust as well as drive efficiencies and reduce costs as they deliver AI-ready data across their organization. Whether you’re scaling data operations or just getting started, dbt empowers your team to move from raw data to actionable analytics with confidence.

Enterprises rely on Kyvos for blazing-fast analytics at massive scale, reliable AI + BI, rapid data exploration, cost efficiency and modernization of underperforming analytics systems, including OLAP. Built on a fully distributed, elastic architecture, Kyvos leverages AI-powered smart aggregation and ultra-wide, deep semantic models to deliver sub-second query performance on billions of rows — while optimizing for cost. It provides a unified semantic foundation for 100% context-aware, enterprise-grade conversational analytics and AI agents, ensuring the highest accuracy and trust at scale.

With ready access to the richest flexible semantic layer, explainable AI, and reusable data modeling, data engineers and scientists can be 95% more productive — create and expand semantic data models, understand any data interrelationship, and run federated queries to speed time to insight. Stardog offers the most advanced graph data virtualization and high-performance graph database — up to 57x better price/performance — to connect any data lakehouse, warehouse or enterprise data source without moving or copying data. Scale use cases and users at lower infrastructure cost. Stardog’s inference engine intelligently applies expert knowledge dynamically at query time to uncover hidden patterns or unexpected insights in relationships that enable better data-informed decisions and business outcomes.

Reshape how everyone accesses, manages, and acts on data and insights by connecting every data source and analytics service together—on a single, AI-powered platform. All your data. All your teams. All in one place. Establish an open and lake-centric hub that helps data engineers connect and curate data from different sources—eliminating sprawl and creating custom views for everyone. Accelerate analysis by developing AI models on a single foundation without data movement—reducing the time data scientists need to deliver value. Innovate faster by helping every person in your organization act on insights from within Microsoft 365 apps, such as Microsoft Excel and Microsoft Teams. Responsibly connect people and data using an open and scalable solution that gives data stewards additional control with built-in security, governance, and compliance.

Source & Match automatically matches the best candidates and jobs across internal and external databases. Through our semantic layer and sophisticated data enrichment everyone becomes an expert sourcing specialist. We find what you mean, not just what you type, making it easy to discover the best talent or jobs. Plus, our powerful matching engine, integrated into your ATS, CRM, Internal Mobility or Talent Management platform, automatically transforms a job posting or candidate into a comprehensive search query providing results with a shortlist of promising candidates or jobs. Our matching accuracy is the game-changer as it provides results you can rely on! - Unlock the full value of your talent and jobs database - Automate with confidence - Eliminate bias Source & Match products redefine the hiring process by enhancing efficiency, elevating the candidate experience, and empowering organizations to turn their talent data into a valuable asset.

Timbr is the ontology-based semantic layer used by leading enterprises to make faster, better decisions with ontologies that transform structured data into AI-ready knowledge. By unifying enterprise data into a SQL-queryable knowledge graph, Timbr makes relationships, metrics, and context explicit, enabling both humans and AI to reason over data with accuracy and speed. Its open, modular architecture connects directly to existing data sources, virtualizing and governing them without replication. The result is a dynamic, easily accessible model that powers analytics, automation, and LLMs through SQL, APIs, SDKs, and natural language. Timbr lets organizations operationalize AI on their data - securely, transparently, and without dependence on proprietary stacks - maximizing data ROI and enabling teams to focus on solving problems instead of managing complexity.

MetaCenter enables business and technology teams to catalog and classify an organization's information assets. Users can self-service questions about their data assets and how data flows through the business and classify how it should be used. This enables organizations to lower costs while improving agility and reducing operational risks. Search-based semantic layer automates cross-referencing models. Faceted Views of specific data assets can be published to individual roles. Lower cost of ownership and higher levels of automation deliver superior ROI compared to competing solutions. Simple GUI driven customization enables rapid application customization. No programming or professional services are required.

Easily connect financial data, customer data and third-party apps to our unified platform. No complex setup required. Effortless tracking and analyzing all your business data, driving informed decision-making and growth. Our semantic layer infuses meaning into your data, making it readily understandable for business users. We provide you with a comprehensive view of your business performance, enabling you to see areas for improvement and optimize operations. Identify patterns in expenses, revenue streams and cash flow trends to gain a deeper understanding of your financial health. Understand customer behavior, including purchase patterns and payment cycles. Track key metrics to assess your startup's progress and make data-driven adjustments to your strategy.

Kater is built for data professionals and data inquisitors. All organized data products are immediately usable by anyone who has a data question, without knowing a lick of SQL. Kater aims to bridge the ownership of data across all business domains in your company. Butler securely connects to your data warehouse's metadata and objects to help you code, discover data, and so much more. Optimize your data for AI with automatic intelligent labeling, categorization, and data curation. We help you define your semantic layer, metric layer, and general documentation. Validated answers are stored in the query bank for smarter, more accurate responses.

Make data-driven decisions 10x faster with self-service analytics. Integrate with your databases and data warehouses all-in-one place (Postgres, MySQL, Snowflake, BigQuery, and more). Brewit can write SQL queries and create recommended charts based on your data questions. It also helps you drill down on the analysis. Chat with your database, visualize insights, & perform analysis. Ensure answer accuracy and consistency with a built-in data catalog. An automated semantic layer that ensures Brewit answers with correct business logic. Easily manage your data catalog & data dictionary. Building a beautiful report is as easy as writing a doc. Data without a story is useless. Our Notion-style notebook editor allows you to create reports & dashboards easily, turning raw data into actionable insights. All organized data products are usable by anyone who has a data question, regardless of their technical skills.

Codd AI solves one of the biggest problems in analytics: making data truly business-ready. Instead of teams spending weeks manually mapping schemas, building models, and defining metrics, Codd uses generative AI to automatically create a context-aware semantic layer that aligns technical data with your business language. That means business users can ask questions in plain English and get accurate, governed answers instantly—through BI tools, conversational AI, or any endpoint. With governance and auditability built in, Codd makes analytics faster, clearer, and more trustworthy. Codd AI ingests both technical metadata from your database, as well as business rules and logic to use AI to auto-generate the most comprehensive semantic layer. This semantic layer is embedded in an intelligent query agent to power natural language (NLP) conversational analytics or power traditional BI tools

CData’s AI offering is centered on Connect AI and associated AI-driven connectivity capabilities, which provide live, governed access to enterprise data without moving it off source systems. Connect AI is built as a managed Model Context Protocol (MCP) platform that lets AI assistants, agents, copilots, and embedded AI applications directly query over 300 data sources, such as CRM, ERP, databases, APIs, with a full understanding of data semantics and relationships. It enforces source system authentication, respects existing role-based permissions, and ensures that AI actions (reads and writes) follow governance and audit rules. The system supports query pushdown, parallel paging, bulk read/write operations, streaming mode for large datasets, and cross-source reasoning via a unified semantic layer. In addition, CData’s “Talk to your Data” engine integrates with its Virtuality product to allow conversational access to BI insights and reports.