Discover how a pull‑based, demand‑driven pipeline maximizes throughput with back-pressure controls.| Sequin blog
We added functions to Sequin so you can filter, transform, and route messages in your CDC pipeline. Learn how they work and why we chose to build Mini Elixir to power them.| Sequin blog
In no such thing as exactly once delivery, we discuss how exactly-once delivery is an asymptote: something a system can approach, but never guarantee 100% of the time. Network partitions and crashes make it impossible to ensure a downstream system saw an event precisely once. A tempting – almost nihilistic – take-away| Sequin blog
Learn about the different PostgreSQL logical decoding output plugins (pgoutput, test_decoding, wal2json) with practical examples showing how each formats database changes for Postgres CDC pipelines.| Sequin blog
Learn the key differences between Debezium's Kafka Connect, Server, and Engine options to choose the right CDC solution.| Sequin blog
Learn how to install and run Debezium Server for Postgres CDC. In this step-by-step tutorial you'll configure Postgres and send changes to a webhook using Debezium Server.| Sequin blog
Learn how to set up Postgres CDC with Debezium to capture database changes in real-time. This hands-on tutorial walks through configuration, streaming, and practical use cases.| Sequin blog
Learn how different sandbox options for user code compare. Explore VM-based options like Lambda, embedded languages like Lua, and more. Which is fastest and easiest to run?| Sequin blog
A complete guide to Postgres CDC that helps you understand how CDC works, performance and features tradeoffs, implementation approaches and off the shelf options, and more.| Sequin blog
Learn how Debezium captures changes from PostgreSQL using the write-ahead log (WAL) for reliable CDC. Understand the benefits and limitations of Debezium's approach and discover how next-generation solutions are improving performance and simplifying operations for database change data capture.| Sequin blog
Learn how Sequin implements Postgres logical replication with guaranteed message delivery and ordering. Discover how we built a high-throughput data pipeline without missing events.| Sequin blog
The biggest problem most startups face is trying to find product/market fit. The key to discovering product/market fit is rapid iteration. You need to build, measure, and adapt quickly based on customer feedback. Ruby on Rails understood this well, and bootstrapped tons of really big companies. The top| Sequin blog
In change data capture, consistency is paramount. A single missing or duplicate message can cascade into time-consuming bugs and erode trust in your entire system. The moment you find a record missing in the destination, you have to wonder: is this the only one? How many others are there? Sequin| Sequin blog
Diátaxis recently made the front page of HN. I mentioned in a comment that we applied the framework to Sequin a couple weeks ago and were very happy with it. Some folks asked me to expand on my comment, so I'm doing so here: The engineer's documentation fallacy Engineers often| Sequin blog
We're building Sequin, a Postgres CDC tool to streams and queues like Kafka, SQS, HTTP endpoints, and more. Efficient, correct pagination is paramount for our backfill process, so we use keyset cursors extensively. You've probably heard about the limitations of offset/limit in Postgres. There are two primary concerns with| Sequin blog
Learn how to implement the request-reply pattern in Postgres. Builds off tools like listen/notify.| Sequin blog
Debunking the myth of "exactly-once delivery." Learn the real differences between messaging system guarantees and what they mean for your architecture.| Sequin blog
Learn how to build your own Postgres-based streaming system. You might not need Kafka or SQS!| Sequin blog
Discover why Phoenix LiveView + Svelte is so fast and productive. Learn our production implementation tips and performance insights.| Sequin blog
We're Sequin, an open source message stream like Kafka, but built on Postgres. Stable, sequential ordering is a very useful thing to have when building a streaming system. But Postgres' behavior here can be surprising! We go down the rabbit hole below. An under-appreciated fact is that while MVCC (multi-version| Sequin blog