Tinybird blog

Building In Public

Hype v. Reality: 5 AI features that actually work in production

It's hard to sift through all the AI hype. Here are 5 AI features you can build that add immediate value to your app.

ClickHouse

I've operated petabyte-scale ClickHouse® clusters for 5 years

I've been operating large ClickHouse clusters for years. Here's what I've learned about architecture, storage, upgrades, config, testing, costs, and ingestion.

Tinybird Examples

Real-time inventory management with lambda architecture

Learn how to use Tinybird to build a lambda architecture for real-time inventory, unifying batch and real-time workflows in a single platform.

Building In Public

Instrument your LLM calls to analyze AI costs and usage

If you're building AI features, make sure to instrument your LLM calls so you can analyze costs, usage, and adoption. Here are a few examples in Python and TypeScript.

Tinybird Examples

Vibe code tools, not toys.

How I vibe coded an internal anomaly detection system that had previously taken me months to build and deploy.

Tech

The simplest way to count 100 billion unique IDs: Part 1

How to build a simpler, real-time version of Reddit's complex system for counting unique IDs, involving Kafka, Redis, and Cassandra.

Forward

Run Tinybird on your own infrastructure

You can now run Tinybird on your own infrastructure, for free, with Tinybird Self-Managed.

Forward

Less ceremony, more shipping

Deployments in data finally get their due. With tb deploy, live schema migrations happen painlessly and automatically.

Forward

Writing tests sucks. Use LLMs so it sucks less.

Testing is a fundamental software practice. But people don't do it in data because it's hard. We're making it less hard (and more fun).

Build fast software with big data requirements

Somehow we got stuck on the idea that big data systems should be slow. We're making it fast.

Forward

Vibe data engineering

You're probably sick of hearing people talk about "vibe coding", but what about "vibe data engineering?" ;)

Forward

Local first.

Run Tinybird on your machine. Deploy your data project locally or to the cloud in the exact same way, as it should be.

Building In Public

Forward: Evolving Tinybird for the AI-native developer

Announcing Tinybird Forward, a new evolution of the Tinybird user experience designed to make building real-time data applications faster and more intuitive than ever before.

Tech

How to run load tests in real-time data systems

We have run hundreds of load tests for customers processing petabytes of data in real-time. Here's everything you need to know to plan, execute, and analyze a load test in a real-time data system.

ClickHouse

We added the Backup Database engine to ClickHouse

We added a new ClickHouse engine: Backup. Here's why we did it, how it's implemented, and example usage.

Outgrowing Postgres

Outgrowing Postgres: How to optimize and integrate an OLTP + OLAP stack

Navigate the complexities of OLTP and OLAP integration by choosing simple, scalable data movement patterns that reduce infrastructure overhead and keep your focus on building great products for users.

Building In Public

You built a Datadog alternative. Now scale it.

I bootstrapped a logs explorer, but I knew it wouldn't scale. Here's how I optimized the data pipeline for billions of logs and thousands of users.

Building In Public

Build a Datadog alternative in 5 minutes

I built an open source template that you can use to have a free, simple Datadog alternative in about 5 minutes. Here was my process for building it.

Building In Public

The perfect data ingestion API design

If you ask me, this is pretty much perfect.

Tinybird Examples

I've helped huge companies scale logs analysis. Here’s how.

I've spent years optimizing logs explorers across multiple domains with trillions of logs to process. Here's what I've learned about building a performant logs analytics system.

Outgrowing Postgres

Outgrowing Postgres: How to evaluate the right OLAP solution for analytics

Moving analytical workloads off Postgres? Learn how to evaluate real-time OLAP solutions based on what actually matters: performance, SQL compatibility, and developer experience.

Tinybird Examples

Build a data-intensive Next.js app with Tinybird and Cursor

Building a Next.js app is easy. Setting up infra to handle millions of logs isn't. Here's how I built a data-intensive Next app with Tinybird and Cursor.

Building In Public Featured

Ship data as you ship code: Deploy changes with a single command

We've redesigned the Tinybird CLI, codename "FORWARD". You can now test it in beta.

Outgrowing Postgres

Outgrowing Postgres: When to move OLAP workloads off Postgres

Learn when to move analytics off Postgres by watching for technical and team health warning signs before crisis hits.

Building In Public Featured

Ship data as you ship code: Tinybird is becoming local-first.

Tinybird's local-first experience is coming. Write code. Test it locally. Push it to git. CI runs the build. It's deployed. You're done.