The Streaming Intelligence Platform. 🚀 Unified Apache Pulsar & Native Kafka powered by the Ursa Engine. 0 cross-AZ costs. 100% Lakehouse-native.
San Francisco, CA
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Streaming guarantees should come with evidence.
We built Streaming Proof to verify delivery, ordering, duplicates, and exactly-once behavior while real failures are happening. Now it’s open source under Apache 2.0 for the broader streaming community to use and extend.
Come build with us 🚀
github.com/openlakestream/st…
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Streams shouldn’t stop at transport.
The new Stream Materialization Framework turns streaming data into governed, queryable assets — from Iceberg and Delta tables to ClickHouse and OpenSearch — without a separate pipeline for every destination.
A simpler foundation for real-time data infrastructure. 👇
What if turning a stream into a queryable data asset didn’t require another connector or pipeline?
Introducing the Stream Materialization Framework from Lakestream!
Declare what your stream should become — Iceberg/Delta tables, ClickHouse tables, OpenSearch indexes, and more — and materialize it directly from object storage during compaction.
Fewer moving parts. Built-in governance. Pluggable by design.
Read more ↓
hubs.ly/Q04ydRlC0
#DataStreaming #ApacheIceberg #Lakehouse
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StreamNative retweeted
Lakehouses are great at telling you what happened. They're not built for what's happening right now, and that's exactly the gap AI agents are exposing.
Join Redpanda's Peter Corless as he moderates a panel with Redpanda's Matthew Schumpert, @streamnativeio's Kundan Vyas, and @VervericaData's Fabian Wilckjens on next week's episode of Data & AI Weekly.
They're digging into what it actually takes to build a Streamhouse architecture, and what's next for the Streamhouse Working Group.
📺 Tune in live on Tuesday, September 29 → bit.ly/4qoGyOp
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💡 How do you make AI infrastructure billing both real-time and financially accurate?
At #DSS2026, Abhinav Wagle of Together AI (@togethercompute) will share a streaming-native architecture built on Kafka, Flink & Iceberg that cuts billing latency from 1+ hours to under 60 seconds.
📅 Oct 7–8 | San Francisco
🔗 hubs.ly/Q04y7-ct0
#DataStreaming #ApacheFlink #ApacheKafka #DSS
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🚀 What if operating Flink started with a conversation?
At OpenAI, #Codex is now the default interface engineers use to understand, debug, and operate Flink pipelines.
At #DSS2026, Stella Gai will share how Codex-native tooling is making stateful stream processing easier to understand, faster to debug, and safer to operate at scale.
🔗 Explore the agenda hubs.ly/Q04y7V3L0
#ApacheFlink #OpenAI #Codex
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A big milestone for StreamNative and the broader streaming community: Ursa and UFK are now open source. 🌊
We believe the future of streaming needs an open, interoperable storage foundation — one that decouples data from brokers and protocols and gives developers more flexibility in how they build.
Excited to open up Ursa, UFK, and the Lakestream API/spec and build this ecosystem together with the community.
Streams need what tables got.
Come build with us. 🌊
streamnative.io/blog/open-so…
🚀 Ursa and UFK are now open source.
We’re opening up the core of StreamNative’s next-gen stream storage architecture:
🔹 Ursa — a stream storage engine built around object storage
🔹 UFK — Kafka-compatible streaming with a diskless architecture
🔹 Lakestream API/spec — an open interface for interoperable stream storage
Our thesis: streams need what tables got — an open storage foundation that decouples data from brokers and protocols.
Come build with us. 🌊
hubs.ly/Q04y6-Hh0
#ApacheKafka #ApachePulsar #Ursa #UFK #OpenSource #DataStreaming
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⚡ #DSS2026 Session Highlight: MCP Is Not Free Context
MCP makes agent integrations composable—but every tool, schema & result competes for the model’s context window.
Experts from OpenAI will explore how to build MCP systems with context budgets in mind:
🔎 Lazy discovery
📦 Compact schemas
⚙️ Server-side filtering
📖 Progressive disclosure
👉 Don't miss out! Register now: hubs.ly/Q04y3xGD0
#MCP #AIagents #Codex
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⚡ #DSS2026 Session Highlight
How does SK Telecom turn streaming data from tens of millions of users into decisions within seconds?
Cazen Lee + Seungbum Lee will share how they combine:
🌊 Apache Flink
🎯 Real-time per-user decisioning
🤖 AI agents + RAG
📊 Production orchestration & observability
And what worked — and didn’t — when bringing streaming + agents together at carrier scale.
🔗 hubs.ly/Q04y3wLz0
#DataStreaming #AIagents #ApacheFlink
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Very excited to have @RisingWaveLabs joining #DSS2026 as a Platinum Sponsor! 🙌
We’re also excited about what we’re building together with SQL Workspace — bringing SQL-powered stream processing across Kafka and Pulsar with RisingWave.
For anyone interested in a closer look, check out the introduction to SQL Workspace here: streamnative.io/blog/introdu…
Looking forward to continuing the conversation in San Francisco! 👉datastreaming-summit.org/dss…
For the first time in the last twelve years, there’s no Confluent but Confluent, an IBM Company.
Confluent's founders introduced Kafka to the world, and their team also helped establish it as an industry standard in the data space.
Today, more than 80% of all Fortune 100 companies and more than another hundred thousand companies use Kafka, and the whole market is worth billions of dollars.
There are also some other big developments happening in our space, such as:
Streamhouse Initiative (the unification of streaming and Iceberg Lakehouse, which means the duality of streams and Iceberg tables and querying both with SQL).
Consolidation in data streaming
Confluent Cloud (Kafka + Flink)
Redpanda SQL (Redpanda + Oxla)
StreamNative’s SQL Workspace (Kafka and Pulsar + RisingWave).
Also, the rise of Agentic AI that’s changing all industries across the board and is also bringing new challenges and opportunities to our space.
Against this backdrop, the data streaming and stream processing community is coming together to meet and have a discussion about all these developments in our space.
We’re really excited to support Data Streaming Summit 2026 as a Platinum Sponsor!
Join us to explore all of the above and much more, and to connect with the community members building all this!
Register here: datastreaming-summit.org/dss…
We look forward to seeing you there!
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Bridging the gap between real-time streams and years of historical data doesn't require a messy Lambda architecture. ⚡️📊
Catch ChinmaySoman (@startreedata) & KundanVyas (@streamnativeio) at #DSS2026 as they break down full-spectrum analytics with #StreamNative, Apache #Iceberg, & #StarTree.
#DataEngineering #ApacheIceberg #DSS
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Learn how to query fresh stream events & historical Iceberg tables with sub-second latency—no data re-ingestion required.
👉 Register here: datastreaming-summit.org/dss…
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⚡ #DSS2026 Session Highlight
Apache Flink scales — but how do you make it more efficient?
Join Yaroslav Tkachenko for “Lessons Learned: Vectorizing Apache Flink” and explore:
🔹 Columnar vs. row-based execution
🔹 SIMD & native acceleration
🔹 Flink → Substrait → Apache DataFusion
🔹 Extending batch engines for streaming workloads
Learn how these optimizations can translate into meaningful performance gains and cost savings.
🔗 hubs.ly/Q04xY1L70
#ApacheFlink #DataStreaming #StreamingSQL
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🏆 Compete for a $5,000 top prize at #DSS2026!
Join the Data + Agent Hackathon and build a real-time AI agent in one day.
💡 Bring your idea
🛠️ Get hands-on support
🚀 Build + demo your agent
👥 Solo builders & teams welcome
🎟️ Only 50 spots
👉 hubs.ly/Q04xN6f80
#Hackathon #AIAgents #DataStreaming
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🤝 Meet the sponsors powering #DSS2026 — The Data+Agent Conference!
🏆 Platinum: @awscloud · @RisingWaveLabs
🥇 Gold: @getconduktor · @GreydientL
🥈 Silver: @puppyquery
🌐 Plus an amazing group of Community Sponsors
A huge thank you to all of our sponsors for supporting DSS 2026 and helping bring the data + AI community together! 🙌
And there’s more to come — additional sponsors will be announced soon. 👀
Join us Oct 7–8 in San Francisco.
👉 hubs.ly/Q04xMPbk0
#DataStreaming #AIAgents #RealTimeData
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🎯 #DSS2026 Session Highlight
At #DataStreamingSummit 2026, experts from @NVIDIA will share practical patterns for building multimodal AI infrastructure across real-time inference and batch replay.
Featuring Ray, NVIDIA Dynamo, backpressure, autoscaling, caching & more.
👉 Explore the full agenda & Register: hubs.ly/Q04xGq0d0
#NVIDIA #AIAgents #MultimodalAI #AIInfrastructure
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How do you build a data agent across 70,000 datasets and 600+ PB of data?
At #DSS2026, Bonnie Xu from @OpenAI will share how they built an in-house data agent that combines curated context + live inspection to turn questions into insights in minutes.
Learn how OpenAI approaches context freshness, evaluation, permissions, and reliable data agents at enterprise scale.
#AIAgents #DataEngineering #OpenAI
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Explore the full agenda & Register: datastreaming-summit.org/dss…
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