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

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

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

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.

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...

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

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

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

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...

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

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

Materialize 25.2 is here!

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

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

Just a normal day at work where a co-worker discovers a memory bug in Rust

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

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

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.

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

YouTube video by Frank McSherry Looking at Bluesky live on Materialize

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...

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

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...

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...

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).

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

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.

🚀 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

Materialize's Strong Consistency Guarantees for Continually Changing Data Learn how Materialize brings order to views over independent, continually changing, transactional data sources

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

Replica expiration: Limiting temporal filters' resource requirements Replica expiration is a new feature in Materialize that limits the resource requirements of temporal filters.

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

We just landed the first use of the columnar crate in Materialize! Stay tuned for more.

github.com/MaterializeI...

@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

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/

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

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

@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