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Materialize

@materialize.com
100 followers 3 following 35 posts

The live data layer for agents and apps

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Materialize @materialize.com · 02/03/2026
Operational data changes continuously. Iceberg was built for batch commits. Materialize’s Iceberg sink delivers transactionally consistent operational data into Iceberg without the memory and latency costs of batching. If Kappa means compute once and serve everywhere, this is how. 🔗 bit.ly/4r4j9QI
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Materialize @materialize.com · 07/01/2026
Agents don’t fail in production because models are bad. They fail because context is stale, fragmented, or too slow. See how Day AI built an agentic CRM, with live context powered by Materialize 🔗 bit.ly/3Ytjr8e
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Materialize @materialize.com · 20/11/2025
Flare needed fresher, unified data as microservices bottlenecks slowed development. With Materialize + dbt, they built a live data layer across all systems, enabling sub-second queries, unified case views, a reliable “My Clients” dashboard, and fast features for AI-driven matching. bit.ly/4iuQUs9
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Materialize @materialize.com · 02/10/2025
Not all operational data platforms are built alike. We break down the trade-offs between Materialize and Palantir Foundry in a new white paper. 📖 bit.ly/46LTjsO
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Materialize @materialize.com · 22/09/2025
Vector databases need fresh context to be useful. The challenge: keeping attributes up to date without burning compute or building brittle pipelines. Materialize fixes this with incremental updates, giving you faster, cheaper, fresher vector search. bit.ly/3KddzMs
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Materialize @materialize.com · 18/09/2025
We’ve released a major improvement to our memory spilling infrastructure: Materialize now uses swap to scale SQL workloads beyond RAM. ✅ Faster hydration ✅ Efficient memory utilization ✅ Bigger workloads supported Full post from antiguru.bsky.social → bit.ly/46EF2iJ
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Materialize @materialize.com · 13/08/2025
New white paper: Materialize vs ClickHouse How to choose the right tool for real-time vs historical analytics — and why modern data platforms often need both. Dive into architectural comparisons, use cases, and case studies: bit.ly/412qx5b #DataInfrastructure #ClickHouse #Materialize #AIDataLayers
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Materialize @materialize.com · 11/08/2025
Waiting for CI hurts. In July, we cut our runtime by up to 86%. From 23+ min builds to under 2 min, and full runs in as little as 7 min. Caching, parallelization, smarter builds, and a bit of [libeatmydata] magic. How we did it 🔗 bit.ly/45yoOWM
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Materialize @materialize.com · 04/08/2025
AI agents need more than stale snapshots — they need a real-time model of the world. Materialize powers digital twins: always-fresh, SQL-accessible representations of your business. How to build them: bit.ly/46H97i7
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Materialize @materialize.com · 31/07/2025
Materialize can "push down" the filters in your query to its storage layer to fetch less data — and thanks to a few cool static analysis tricks, this works for more queries than you might expect. To see how it works, check out the blog: bit.ly/475FBCL
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Materialize @materialize.com · 17/07/2025
Want live analytics on Bluesky itself? Pipe the public firehose into Materialize with a tiny JS script, then explore trends in SQL. Full walkthrough by @frankmcsherry.bsky.social → bit.ly/46OOwsa
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Materialize @materialize.com · 14/07/2025
Untangling control vs. data paths :point_right: Bigger SELECT results, smaller bottlenecks. Materialize now streams large query outputs out-of-band, so coordination stays snappy while data flies. Dive into the architecture shift and what it unlocks next → bit.ly/3Ub6GwI
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Materialize @materialize.com · 10/07/2025
SponsorCX went from 90-minute batch updates to ~1-second freshness by pointing Materialize at Postgres. No streaming specialists—just SQL. Real-time reporting shipped the same day. Check out the full story: bit.ly/4lM1k6Y
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Materialize @materialize.com · 08/07/2025
Neo Financial now serves real-time features that are fresh and fast while saving 80 % on infra. All SQL, no cluster babysitting. Case study → bit.ly/4lIP8E3
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Materialize @materialize.com · 02/07/2025
Flink vs Materialize isn’t apples-to-apples. Flink is a stream processor with external dependencies. Materialize is a unified platform: ingest, transform, and serve real-time data in SQL. 💡 50% faster deploys 💰 45% lower cost 📖 Read the guide: bit.ly/4eBNMc0
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Materialize @materialize.com · 01/07/2025
LLM agents that act need data that reacts. If your data layer can’t reflect the consequences of an agent’s action in real time, it’s not just inefficient—it can lead to disaster. 🧠 Smarter agents need smarter data. bit.ly/4lz4hro #AI #DigitalTwins #LLM #Materialize
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Materialize @materialize.com · 25/06/2025
Materialize 25.2 is here! New features include live freshness reports for all your views, 2.5x faster data product deployment times, and native SQL Server support. See how these updates can help streamline your operations: bit.ly/44i2hg2
Materialize 25.2 is here!
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Materialize @materialize.com · 02/06/2025
Big news: Materialize now connects directly to SQL Server. We ingest CDC, maintain real-time views of your logic, and eliminate the pain of: - Slow OLTP queries - Stale dashboards - Brittle pipelines Just SQL. Just correct. Just live. 🔗 bit.ly/4mKbk1S
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Materialize @materialize.com · 15/05/2025
The Materialize engineering team uncovered a rare concurrency bug 🪲in Rust’s 🦀 unbounded channels that could lead to double-free memory errors. After thorough debugging and working with the Rust and crossbeam communities, the fix is now part of @rust-lang.org 1.87.0. 🔗 bit.ly/3Fan1Om
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Materialize @materialize.com · 15/05/2025
AI is pushing data infrastructure to its limits. MCP gives agents access to services—including databases—but most systems can’t handle the load. Materialize’s MCP server turns live data products into tools agents can use—without crushing your systems or overwhelming your team. bit.ly/4jYBrQU
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Materialize @materialize.com · 11/03/2025
Materialize for Everyone: Now Self-Managed & Free 💡 Self-Managed – Deploy in your own cloud, full control. 💡 Community Edition – Production-grade Materialize, free forever. Real-time data is now open to all. Learn more: bit.ly/43Bg8iQ
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Materialize @materialize.com · 21/01/2025
Want AI that acts, not just informs? 🚀 Discover how Materialize delivers real-time, consistent structured data to supercharge RAG systems. Say goodbye to stale insights and hello to AI that drives action. Read more: bit.ly/4anPBHl #AI #RAG #RealTimeData
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Materialize @materialize.com · 16/01/2025
Simplifying microservices data integration—without compromising performance or scalability—is possible. Check out our new blog on shared databases, materialized views, and redefining microservices architecture with Materialize. Learn more: bit.ly/4jhHG2g
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Materialize @materialize.com · 15/01/2025
@frankmcsherry.bsky.social is revisiting his first Rust crate—columnar—and sharing how he’s updated it to solve complex memory layout challenges with modern, safe Rust. When: Jan 21 | 6:30 PM (🍕), 7:30 PM (🎤) Where: Materialize HQ Love Rust or clever systems design? Join us! bit.ly/3PCNype
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Materialize @materialize.com · 17/12/2024
Self-Managed Materialize is here—early access is open. Run Materialize in your private cloud or wherever your infrastructure demands. Maintain real-time capabilities while keeping full control over your data. Learn more about how it works: bit.ly/3ZXVnM3
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Materialize @materialize.com · 11/12/2024
Are microservices worth the hype? They promise flexibility but bring data consistency issues and hidden overhead. Our blog dives into the challenges and a better way forward with real-time data: 🔗 bit.ly/3VCuzyn #Microservices #RealTimeData
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Materialize @materialize.com · 03/12/2024
materialized views and it's the same but there's incremental updates so it's not Stop by booth #1761 to hear how Materialize is re:Inventing the Operational Data Store. #AWSreInvent #Materialize #RealTimeData #GenerativeAI #Brat #materializedviews #incrementalupdates
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