StreamNative

🎄✨Happy Holidays from StreamNative! ✨🎄 As we wrap up the year, we want to take a moment to say THANK YOU! To our valued customers, dedicated partners, and the vibrant community - your trust, collaboration, and support made 2025 an incredible year for StreamNative. Whether you’ve been with us from the beginning or joined us along the way, we’re grateful to be building the future of data streaming together.♥️ Wishing you and your loved ones a joyful holiday season and a bright, successful year ahead. We can’t wait for what’s next—together. 🚀 #StreamNative #DataStreaming #RealtimeData #HappyHolidays #MerryChristmas

🎄 December Data Streaming Newsletter is here! As we wrap up the year, we’re excited to share a holiday edition packed with meaningful improvements across security, performance, and cloud operations—all designed to help you head into the new year with confidence. What’s inside this month: 🔐 AuthV2 & expanded mTLS support for stronger, more flexible security ⚡ Performance and reliability improvements across Pulsar 🔄 Better Kafka compatibility, observability, and operability ☁️ Cloud Manager enhancements, including new dashboards, safer workflows, and Cluster Profiles for workload-based cost and performance tuning Plus: 🏅 Industry recognition — StreamNative named a Forrester Wave™ Contender with top scores in Messaging and Resource Optimization 📰 In the news — our CEO Sijie Guo shares insights on SQL-first streaming and AI-native data infrastructure in VMblog and SD Times Catch all the details in our December newsletter and release notes. 👇 Thank you for building with us this year—and wishing you a relaxing holiday season and a strong start to the year ahead. 🌟 #DataStreaming #RealtimeData #ApachePulsar #Kafka #StreamingData #StreamNative #ProductUpdates #HolidaySeason

💥 One platform. Two cluster profiles. Clearer choices.💥 We just simplified how StreamNative Cloud clusters are defined—shifting from engine-centric names to workload-driven Cluster Profiles. Introducing: ⚡ Latency-optimized clusters - for predictable, real-time performance 💰 Cost-optimized clusters - for efficient streaming with higher latency tolerance This change reflects our move toward a unified platform that delivers innovation without added complexity.🚀 🔗 Read the blog to learn why we made this change and how to choose the right profile for your workloads: https://hubs.ly/Q03YX9XW0 #StreamingData #RealTimeData #CloudArchitecture #StreamNative

Every year, I make it a point to read a lot of research papers in the data platform/ software engineering space. And then I break them down, connect the dots, and share the ideas back with the community in a more approachable way. Here are 5 papers I genuinely enjoyed this year and think are worth your time ✅ Ursa: A Lakehouse-Native Data Streaming Engine for Kafka: https://lnkd.in/gnVxys2P (by StreamNative) ✅ Velox - Meta's Unified Execution Engine: https://lnkd.in/g6beRwsD (by Meta) ✅ Big Metadata - When Metadata is Big Data: https://lnkd.in/gW9uPRcC (by Google) ✅ Disintegrated State Management in Apache Flink 2.0: https://lnkd.in/g2hwThJb (by Alibaba Group, et. al.) ✅ Lance - Efficient Random Access in Columnar Storage: https://lnkd.in/g9wb83t6 (by LanceDB) #dataengineering #softwareengineering

🎥 Watch Shiyan Xu from Onehouse dive into high-throughput streaming Lakehouses with #ApacheHudi! Learn how Hudi’s streaming-first designs—Merge-on-Read tables, record-level indexing, async compaction, and NBCC concurrency—enable scalable, low-latency, and conflict-free streaming. ▶️ Watch the recording now!
https://hubs.ly/Q03YJSpp0 #DataStreaming #RealTimeData #DSS

How do you manage schemas, data contracts, and streaming data products as your event-driven architecture evolves? In this #DSS session, Jan Siekierski breaks down: ❇️ Practical schema evolution strategies in streaming systems ❇️ Using data contracts to improve governance and trust ❇️ Applying data product principles to real-time data 🎥 Watch the recording and learn how to build streaming data products that scale and evolve with confidence: https://hubs.ly/Q03YBjkf0 #DataStreaming #RealTimeData #DSS #datastreamingsummit

💥 First year. First Wave. Real impact.💥 We’re honored to be recognized in The Forrester Wave™: Streaming Data Platforms, 2025 — in our first year of evaluation! This is a meaningful milestone that reflects our focus on real-world streaming performance, cost efficiency, and production-ready innovation.🚀 👉 Read the blog for more details on why this milestone matters and how it reflects our long-term vision for enterprise streaming. https://hubs.ly/Q03YB8gz0 👉 Access the full report: https://hubs.ly/Q03YB8vB0 #DataStreaming #Forrester #StreamNative #Kafka #Pulsar #Ursa

🧐 How does Uber safely deploy #ApacheFlink jobs at massive scale? In this #DSS25 session, Yao Li and Yusheng Chen from Uber walk through Uber’s Safe Deployment Framework for Flink, built to protect production systems running: ⚡ 4,500+ Flink workflows ⚡ 4+ trillion messages per day ⚡ 99.99% availability requirements 💡 Learn how Uber applies incremental rollouts, automated guardrails, end-to-end testing, and rollback triggers to reduce deployment risk — achieving a 38.5% reduction in incidents caused by bad job code or configs. ▶️ Watch the full recording: https://hubs.ly/Q03YrsqZ0 #DataStreaming #RealTimeData #DSS #datastreamingsummit

Catch Ramnatthan Alagappan (University of Illinois Urbana-Champaign) at #DSS25 as he dives into #LazyLog, a novel shared-log abstraction that significantly reduces ingestion latency for low-latency applications. 💡 Key takeaways: - Defers ordering on append to achieve faster ingestion - Supports use cases like event sourcing, activity logging, and distributed databases - Implements Erwin and Erwin-BB, achieving up to 1M appends/sec with low latency - Offers practical insights for real-time data streaming systems 📺 Watch the full recording here: https://hubs.ly/Q03Ykyff0 #DataStreaming #RealTimeData #DSS #datastreamingsummit