Feldera

⚡️ Shipped This Week We ship big and we ship small. This week was about the details. The kind that makes the engine easier to debug, observe, and run efficiently in production. A few highlights from this week: → Live write progress for Postgres output: Postgres output writes now show live progress in the UI and metrics API. You can tell the difference between a slow write and a stuck one, without guessing. → Connector error messages survive restarts: Error messages from connector failures are now persisted through the checkpoint and restored on resume. After a restart, you have the full error context, not just the counts. → SQL optimizer: The query optimizer now automatically rewrites MAX(CASE expr THEN 1 ELSE 0) into a COUNT-based equivalent that's significantly cheaper to maintain incrementally. No SQL changes required. All of this is live in our sandbox right now: try.feldera.com.

Databases are bad at answering a simple question: “What’s new?” PostgreSQL will happily query your entire dataset. But if you want to know what changed since you last checked, you can’t do this through one of the standard APIs—you have to drop down to the low-level logical replication protocol. Entire ecosystems exist just to bridge this gap. Tools like Debezium solve it well—but at a cost: you end up running and operating additional distributed systems like Kafka and Kafka Connect. That’s why I’m excited about our new #Postgres input connector. It taps directly into the replication protocol—no extra services required, which means a simpler architecture with fewer moving parts. And the best part is that it wasn’t built in-house. This connector was contributed by an OSS community member. Huge thanks to Mohammed Ali for this great contribution 🙌 https://lnkd.in/g7XUWmcS

Good news: you no longer have to wait for DevOps to configure your servers. https://copy.fail/ It should not surprise anyone that AI agents can find (or help to find) bugs in 40 million lines of C code. I expect many more to come. Will it force a migration away from Linux toward safe kernels, maybe even a formally verified one? Sadly it's unlikely happening anytime soon. Projects like this have existed for years, and many are technically very impressive. But unfortunately they have received very little commercial attention compared with Linux. 💸

There's a spicy Reddit thread making the rounds about data engineering frustrations. It’s worth a read: https://lnkd.in/gt-qQh8t - "Everyone wants real-time processing with no real use case." - "Hourly refreshes burn compute and credits for zero business value." - "Being rushed into AI projects when we clearly don't have the resources or architecture for it." A lot of this pain is real. But digging into the comments, it’s not the need for real-time that folks are questioning. It’s the cost. What if you didn't have to pick between sub-second freshness and lower compute costs?

Incremental Updates - April 2026 edition is here!

With RAM prices increasing 4x, "just add more compute and RAM" is not a serious systems strategy.

Another incredible contribution from our OSS community! Mohammed Ali shipped a Postgres CDC input connector for Feldera. Built with crash-safe replication, snapshot and streaming support, and fault tolerance baked in. Postgres pipelines can now read historical data and live changes in a single connector. Postgres is one of the most widely deployed databases in the world. This opens Feldera up to a massive ecosystem of engineers who are already running it in production. Genuinely grateful for contributions like this. Thank you! 🙌 What are you building on Feldera? We’d love to see it. https://lnkd.in/gHgrzN5i

⚡️Shipped This Week More SQL functions. Pipelines got more observable. Memory usage went down. And the Feldera community keeps showing up. Here are some highlights from this week: → Postgres CDC input connector: You can now connect Feldera directly to Postgres via logical replication. Point the connector at your database, and it handles the full table snapshot first, then switches seamlessly to continuous WAL streaming - crash-safe, so if anything goes wrong, the pipeline resumes exactly where it left off with no data loss. Built by Feldera OSS contributor Mohammed Ali (thank you!). → RANK and DENSE_RANK in SQL: Two of the most-requested SQL window functions are now in Feldera; like everything else we do, they are evaluated incrementally. → Pipeline monitoring events: Every pipeline now keeps a continuous event history of up to 5 days of status changes, queryable from the API, CLI, UI or Python SDK. → Control-plane scalability: The extremes that our customers take our software to is truly amazing sometimes. Therefore, we also improved memory usage in the control-plane. This makes for a smoother experience when you want to orchestrate lots of Feldera pipelines. All of this is live in our sandbox right now: try.feldera.com. No infrastructure or setup required.

How do you give AI agents live, actionable signals? Swipe to find out 👉 Run it yourself: https://lnkd.in/gjT6tDAB

Feldera is SOC 2 Type 2 compliant ✅ As a bring-your-own-cloud platform, your data always stays in your infrastructure. SOC 2 Type 2 is our commitment to holding ourselves to the highest security standards. Independently audited by Prescient Security. Full details: trust.feldera.com