StreamNative

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StreamNative

@streamnativeio

The Streaming Intelligence Platform. 🚀 Unified Apache Pulsar & Native Kafka powered by the Ursa Engine. 0 cross-AZ costs. 100% Lakehouse-native.

San Francisco, CA Katılım Kasım 2018
35 Takip Edilen2.4K Takipçiler
StreamNative
StreamNative@streamnativeio·
StreamNative Cloud just launched Maintenance Notifications! 🛠️ Stay ahead of updates with centralized visibility into your Pulsar clusters and cloud environments. What’s new: 🔹 Central Dashboard: Track all planned and ongoing maintenance in the Console. 🔹 Detailed Info: Review change summaries, scheduled windows, and target resources. 🔹 Full Control: Approve, Reject, or Reschedule maintenance (Enterprise/Production plans). 🔹 Email Alerts: Get notified before, during, and after execution. Read the full update: hubs.ly/Q04gDBCY0
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StreamNative
StreamNative@streamnativeio·
The StreamNative Kafka Service (UFK) just got a major upgrade! 💥 We’re expanding the Lakestream vision with more clouds, more semantics, and more deployment flexibility. The Highlights: ✅ Azure Support: Now available on all 3 major clouds. ✅ Kafka Queues: Scale consumers beyond partitions for AI & task orchestration. ✅ Private Cloud: Ursa-powered lakehouse architecture for self-managed environments. ✅ New Pricing: Optimized storage for high-volume analytics. Streamlining Kafka without the operational complexity.🚀 👉 Read more: hubs.ly/Q04gsNxt0 #ApacheKafka #CloudNative #DataEngineering #StreamNative
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StreamNative
StreamNative@streamnativeio·
Final call! 🚨 Join us tomorrow, Thursday, May 14, at 9:00 AM PT, to learn how to bridge the gap between real-time streaming and governed lakehouses with @databricks. We’ll dive into: ✅ Direct writes into Unity Catalog-managed Delta tables. ✅ Streamlined ingestion for Kafka and Pulsar data. ✅ AI-ready architectures for unified data governance. 👉 Save your spot: hubs.ly/Q04gpjwv0 #DataStreaming #Databricks #UnityCatalog #Lakehouse #Kafka #Pulsar #DataGovernance
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StreamNative
StreamNative@streamnativeio·
We’re excited to announce Organization-Level Remote MCP Server support in StreamNative Cloud! We are moving beyond cluster-level boundaries to give developers a unified, governed interface for AI agents. What’s new: 🔹 Unified Access: Connect agents to data across multiple clusters via a single MCP endpoint. 🔹 Centralized Governance: Use organization-scoped API keys (Auth v2) to simplify security. 🔹 Better DX: No more managing fragmented endpoints per cluster. Moving from streaming infrastructure ➡️ intelligent, autonomous systems. Read the full update: hubs.ly/Q04gj40x0 #AI #MCPServer #DataStreaming #StreamNative #GenAI
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StreamNative
StreamNative@streamnativeio·
The Kafka TCO comparison no vendor will run is finally here. 📊 We stripped away the sales fluff to compare Kafka on AWS using published rate cards and real-world assumptions. The result? Pick the wrong latency tier and you could overpay by 4-10x per byte. Inside the report: 🔹 Rankings for sub-10ms workloads. 🔹 How S3 backends are redefining Analytics costs. 🔹 Why a "Pluggable Storage" cluster is 3.5x cheaper than vendor sprawl. 🔹 How to apply AWS EDP/Savings Plans to your bill. 🇬🇧 At #Current26? Grab a physical "Field Guide" at the StreamNative booth and whiteboard your architecture with our experts. Not in London? Link to the full report in the thread below! 👇 #ApacheKafka #AWS #DataStreaming #TCO #CurrentLondon
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StreamNative
StreamNative@streamnativeio·
Heading to #Current London? Don’t miss our session: Diskless Kafka Meets Iceberg Learn how to: ✅ Run Native Kafka on Diskless Storage ✅ Eliminate ETL with Apache Iceberg ✅ Cut costs w/ Lakestream Then, come whiteboard your architecture at the StreamNative booth. Stop by for live demos and exclusive swag! 🇬🇧 #ApacheKafka #ApacheIceberg #DataStreaming #StreamNative
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StreamNative@streamnativeio·
What happens when you remove the local disk from #ApacheKafka? 🤔 Tracing the data flow in Ursa-for-Kafka (UFK): 1️⃣ Protocol Layer: Accumulates records in-memory. 2️⃣ Data Layer: Flushes directly to S3/GCS/Azure (No cross-AZ traffic!). 3️⃣ Metadata Layer: Oxia atomically assigns offsets. 4️⃣ Compaction: Background workers turn WAL data into queryable Parquet. The result? 100% Kafka compatibility with Lakehouse efficiency. [Check the first reply for the full deep dive! 🔗] #Kafka #CloudNative #UrsaStorage #DataEngineering
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