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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 · 22/10/2025
New from Materialize: Cloud M.1 Clusters Run 3x larger workloads with the same low latency and predictable performance—thanks to intelligent data spilling and expanded capacity. Learn more: bit.ly/3L12oH2
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Introducing New Materialize Cloud M.1 Clusters
Introducing a new Materialize Cloud cluster type. M.1 Clusters provide customers with more capacity, leading to better economics and performance, while maintaining the same low latency requirements th...
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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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Sync Conf @syncconf.bsky.social · 19/09/2025
Welcome Frank McSherry @frankmcsherry.bsky.social to Sync Conf 2025. Pioneer of sync technology, inventor of Differential Dataflow, and founder of @materialize.com, Frank will trace the evolution of sync and stream processing.
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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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Frank McSherry @frankmcsherry.bsky.social · 13/08/2025
I wrote about the projects done at Materialize’s recent hackathon. Many very cool projects, and also one that I worked on; take a read! materialize.com/blog/spring_...
materialize.com
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Materialize @materialize.com · 14/08/2025
At our last on-site, the Materialize R&D team held a hackathon. 8 projects. 1.5 days. Highlights: – SQL tutorial game – WASM UDFs – API endpoints from views – S3 as a consensus layer One shipped already. Others might next. Read the full recap → bit.ly/4lo4YmR
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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 · 12/08/2025
That’s Materialize.
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Materialize @materialize.com · 12/08/2025
Imagine… A live data layer built for apps *and* agents That incrementally maintains views at the scale of >1M updates per second While maintaining up-to-the-second freshness With query response times in the single-digit milliseconds
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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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Frank McSherry @frankmcsherry.bsky.social · 16/07/2025
We have a new blog post up at @materialize.com about analyzing the Bluesky firehose (Jetstream, really) through Materialize. You can grab a copy of the community edition of MZ and follow along, or invent your own ways of looking at the data, live! materialize.com/blog/analyzi...
materialize.com
Analyzing Live Social Data: Exploring Social Trends on Bluesky
Bluesky provides a public firehose that we can stream into Materialize, through which we can observe live social behavior and trends.
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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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Frank McSherry @frankmcsherry.bsky.social · 07/07/2025
I refreshed a blog post draft on streaming the Bluesky firehose through @materialize.com. Some experience tidied up the examples, made things a bit more efficient, and told a different story (now with less cloture). More in the near future, as we put a front end on it! github.com/frankmcsherr...
github.com
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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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remember to salt the fries 🍟 🇱🇧🇵🇸🇾🇪 @jasonhz.bsky.social · 15/05/2025
Just a normal day at work where a co-worker discovers a memory bug in Rust
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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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Nate Stewart @nate-stewart.bsky.social · 11/04/2025
Agents generate more data and place more demand on systems than ever before—and standards like MCP will only accelerate this trend. Learn how Delphi is rethinking how they build data-intensive applications—from the db to the UI: bit.ly/42BZdf9
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Scaling queries on agent-produced data: How Delphi transformed its data infrastructure
Join our webinar with Delphi to discover they evolved their data infrastructure to handle the rapid increase in AI-driven interactions with Materialize.
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Frank McSherry @frankmcsherry.bsky.social · 23/03/2025
I just put up a video of me using @materialize.com to ingest and analyze live Bluesky data. Starts with a Javascript bridge to get the data in, and then builds up various live views using SQL. Caveat: it's a live demo with live data. Eek! www.youtube.com/watch?v=T6cY...
youtube.com
Looking at Bluesky live on Materialize
YouTube video by Frank McSherry
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complexsplit.bsky.social @complexsplit.bsky.social · 11/03/2025
at the rustnyc meetup and the vibe is electric! thanks to @materialize.com for hosting. (they just released their self-managed version today!) #rust #rustlang
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Frank McSherry @frankmcsherry.bsky.social · 11/03/2025
I'm very excited to share that @materialize.com now has a Self-Managed option, as well as a Community Edition license that lets you play around with the exact same bits but for free. materialize.com/blog/materia...
materialize.com
Materialize For Everyone: Introducing Self-Managed and our Free Community Edition
Unlock real-time data transformation with Self-Managed Materialize. Now, deploy Materialize in your own cloud for security, compliance, and performance control—powered by the same battle-tested, incre...
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Nate Stewart @nate-stewart.bsky.social · 11/03/2025
To keep up with the demands of AI projects your teams need to transform, deliver, and act on fast changing data no matter where it resides. Today, we’re making that possible by moving Self-Managed @materialize.com out of beta and introducing Materialize Community Edition (CE).
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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 · 05/02/2025
🚀 Debugging Materialize with Materialize 🚀 Materialize now exposes source maps, mapping runtime metrics to high-level operators. ✅ Pinpoint bottlenecks ✅ Get EXPLAIN ANALYZE insights ✅ Tune TopK queries efficiently Deep dive: bit.ly/3Eq2l4g #databases #queryoptimization #Materialize
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Source Mapping and Introspection: Debugging Materialize with Materialize
Materialize now exposes source maps in its catalog, so you can build your own debugging queries that attribute performance characteristics to high-level operators.
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Materialize @materialize.com · 27/01/2025
How does your data system handle constant change? Materialize delivers real-time consistency for evolving, transactional data sources. @frankmcsherry.bsky.social explains how virtual time aligns data timelines for guaranteed accuracy. Learn more: bit.ly/40SZVCX
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Materialize's Strong Consistency Guarantees for Continually Changing Data
Learn how Materialize brings order to views over independent, continually changing, transactional data sources
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Materialize @materialize.com · 24/01/2025
Materialize introduces Replica Expiration! Our latest optimization cuts memory use by up to 50% while maintaining performance and accuracy. 🔗 bit.ly/4aDkdEL #Materialize #StreamingSQL #DataOptimization
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Replica expiration: Limiting temporal filters' resource requirements
Replica expiration is a new feature in Materialize that limits the resource requirements of temporal filters.
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Moritz Hoffmann @antiguru.bsky.social · 22/01/2025
We just landed the first use of the columnar crate in Materialize! Stay tuned for more. github.com/MaterializeI...
github.com
Columnar in logging dataflows by antiguru · Pull Request #30883 · MaterializeInc/materialize
Convert logging dataflows to columnar The aim of this PR is to convert some of the logging dataflows to use columnar data on dataflow edges, wherever it makes sense to do so. It introduces building...
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Robert Balicki @statisticsftw.bsky.social · 22/01/2025
@frankmcsherry.bsky.social at #rustnyc: the main problem with my presentation is that I'm too excited and I'll tell you the story out of order. Let's gooo
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Frank McSherry @frankmcsherry.bsky.social · 22/01/2025
Big thanks to the #rustnyc audience; you all were great! Patience, smiles, and thoughtful questions all around. This happens regularly, so if you are in the NYC area and interested in Rust, keep tabs and show up in the future: www.meetup.com/rust-nyc/
meetup.com
Rust NYC | Meetup
We are interested in the Rust programming language, its ecosystem, and its contributors. We occasionally meet to talk about these things.Find our Discord, live streams, and Rust job matching programs ...
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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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Moritz Hoffmann @antiguru.bsky.social · 15/01/2025
I wrote a bit about efficient maintenance of temporal filters in @materialize.com. By periodically restarting replicas, we can limit resource requirements (RAM and CPU), all without any other user-visible impact. materialize.com/blog/replica...
materialize.com
Replica expiration: Limiting temporal filters' resource requirements
Replica expiration is a new feature in Materialize that limits the resource requirements of temporal filters.
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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 · 16/12/2024
The future of autonomous systems isn’t just smarter agents—it’s intelligent orchestration. 🌐 Learn how Materialize helps AI agents collaborate in real-time, share fresh data, and scale intelligently. Read the blog: bit.ly/4fk1qyT
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Reimagining Agentic Orchestration: Materialize and the Future of Autonomous Systems
Discover how Materialize empowers intelligent agents to collaborate in real-time, ensuring cost-effective and efficient orchestration for autonomous systems. Transform the future of AI-powered ecosyst...
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Josh Arenberg @josharenberg.bsky.social · 11/12/2024
turns out Materialize can help out with microservice architectures... I wrote about it here.
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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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Nikhil Benesch @benesch.bsky.social · 04/12/2024
S3 (Iceberg) Tables is everything I dreamt of, and more. I blogged some long-form thoughts: meltware.com/2024/12/04/s... I think we're about to see an explosion of data tools (@materialize.com, @clickhouse.com, @duckdb.org, et al.) learn to write Iceberg tables via S3 table buckets. #databs
meltware.com
A First Look at S3 (Iceberg) Tables
AWS announced S3 Tables today, which brings native support for Apache Iceberg to S3. It’s hard to overstate how exciting this is for the data analytics ecosystem. This post is a quick rundown of my th...
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