Tinybird blog

Real-time Data

What it takes to build a real-time recommendation system

Real-time recommendation systems power a vast number of modern customer experiences. Learn what it takes to build a real-time recommender in this comprehensive guide.

Real-time Data

Real-time streaming data architectures that scale

Data and engineering teams are turning to real-time data architectures to power revenue-generating data pipelines. This post provides a reference for building scalable streaming data architectures that can support multiple different use cases.

Product

Run analytics on files in Amazon S3 the easy way

So, you want to run analytics on data stored in S3 files? Here’s the easy way to do it, using the Tinybird S3 Connector.

Company

Tinybird connects with Confluent for real-time streaming analytics at scale

Today, Tinybird announces its partnership with Confluent. Read how to use Tinybird & Confluent to build powerful real-time analytics over streaming data.

Real-time Data

16 questions you need to ask about your Real-Time Data Strategy

Considering a real-time data initiative? Answer these 16 questions and follow these recommendations to nail your real-time data strategy.

Tech

Data-driven CI pipeline monitoring with pytest

Recently, we cut our CI pipeline execution time in half. To consummate our work, we've officially published the pytest plugin that made it possible, so you can use it, too.

Tinybird Examples

How to set up event-based ingestion of files in S3 for free

In this tutorial, I'll show you how to use S3 Event notifications and AWS Lambda to trigger downstream workflows when new files are uploaded to S3.

Data 101

Event-driven architecture best practices for databases and files

Event-driven architectures should have largely replaced poll-based workflows and batch ETLs. Here are the common patterns (and anti-patterns) I have observed for event-driven ingestion of data from both application databases and file systems.

Data 101

Using Tinybird as a serverless online feature store

Machine learning can feel like a lot of hype, but feature stores are extraordinarily practical. In this post, I'll show you why Tinybird makes for an excellent online feature store for real-time inference and game-changing user experiences.

ClickHouse

Using Bloom filter indexes for real-time text search in ClickHouse®️

A customer of ours had text-based log data and they wanted to be able to search over the text (quickly). However, in ClickHouse, text search without any special measures involves a full scan, period. And we know that full scans are not efficient.

Tinybird Examples

Designing and implementing a weather data API

When I first learned about Tinybird, its mission of helping developers build APIs caught my eye. I wondered what it would be like to design and implement a weather data API using Tinybird. In this post, I've documented my journey doing just that.

Product

A new way to create intermediate Data Sources in Tinybird

We are pleased to announce the general availability release of Copy Pipes, a new way to generate snapshots of SQL results and store them in a Tinybird Data Source.

Data 101

5 criteria of data quality and how to test for them

Data Quality Assurance is an important focus for companies seeking to advance the trustworthiness of their data pipelines. Here are 5 criteria for measurement data quality, and some sample SQL you can use to test for them.

ClickHouse

Adding JOIN support for parallel replicas on ClickHouse®️

We recently introduced a pull request to ClickHouse that enables simple JOIN support for parallel replicas on ClickHouse. The solution may be simple and naive, but the ceiling for performance on distributed queries just got WAY higher.

Product

Why we just released a huge upgrade to our VS Code Extension

Tinybird is a powerful, performant real-time data platform. But we win the hearts of engineers through an amazing developer experience. Read how and why we recently upgraded our VS Code Extension for an even better DX.

Tech

5 Snowflake struggles that every Data Engineer deals with

Snowflake is the world’s leading cloud data warehouse, but it is almost always slow and costly for application development. Tinybird makes it easy to quickly and cost-effectively build applications on top of your Snowflake data. Tinybird and Snowflake are better together.

Product

Using custom Kafka headers for advanced message processing

Kafka headers are key-value pairs that can be attached to Kafka messages to provide metadata and additional information about the message. Read on to learn more about the use cases headers support and how to build real-time analytics pipelines using Kafka headers.

Data 101

The 8 considerations for designing public data APIs

For years I developed flood warning systems built on public data APIs. From my experience, I learned that there are 8 things you must consider to build a resilient public data API. These are those 8 things, and how Tinybird can take some of them off your plate.

Upgrading short link analytics by 100x with Steven Tey

We sat down with Steven Tey, Senior Developer Advocate at Vercel and creator of Dub.co, to talk about why switched Dub's analytics from Redis Sorted Sets to Tinybird.

Dev Q&As

Building privacy-first native app telemetry with Guilherme Oenning

Guilherme Oenning left his job to create Aptabase, a platform for mobile and desktop app developers to build telemetry and analytics using simple SDKs. We sat down with Guilherme to talk about building Aptabase and why he chose Tinybird over Postgres, BigQuery, and ClickHouse Cloud.

Tinybird Examples

How to build a real-time fraud detection system

Digital fraud affects so many organizations. In this blog post, you'll learn the components of a real-time fraud detection system, and how to build one with Tinybird.

Data 101

The 5 rules for writing faster SQL queries

If you're building real-time analytics, you need your SQL to be fast. Fast SQL queries improve performance and reduce cost. Here are the 5 rules to follow to write the fastest SQL queries of your life.

Low-code analytics with James Devonport of UserLoop

James Devonport chose to build UserLoop on a no-code platform so he could quickly respond to customer feedback. Read how he found and implemented Tinybird on his journey to building the number one eCommerce customer intelligence software.

Tinybird Examples

Automating customer usage alerts with Tinybird and Make

Here's how I used "low-code" analytics and automation to help my team be more proactive.

Our Beliefs

7 strategies we're using to reduce cloud infrastructure costs in 2023

Cloud infrastructure costs are going up for everyone, but expectations to perform haven't receded. Here are 7 strategies that we use at Tinybird to keep our costs low as we innovate new ways to help our customers achieve more with less.