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Tinybird Code
The CLI AI ClickHouse® expert for your projects
tinybird.ai
The analytics backend for your app and agents
Hosted OLAP Database
The world's fastest analytics database without the hassle
APIs
Every query is a scalable and secure REST API
Events API
Stream JSON at 1k+ RPS with an HTTP request
Tinybird Local
Run Tinybird on your machine or your own infra
CLI
Create, build, test, and deploy from your terminal
OpenTelemetry
Ship real-time telemetry without the plumbing
Integrations
Connect to dozens of dev tools and data sources
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Product
Tinybird Code
The CLI AI ClickHouse® expert for your projects
tinybird.ai
The analytics backend for your app and agents
Hosted OLAP Database
The world's fastest analytics database without the hassle
APIs
Every query is a scalable and secure REST API
Events API
Stream JSON at 1k+ RPS with an HTTP request
Tinybird Local
Run Tinybird on your machine or your own infra
CLI
Create, build, test, and deploy from your terminal
OpenTelemetry
Ship real-time telemetry without the plumbing
Integrations
Connect to dozens of dev tools and data sources
Pricing
Docs
Developers
Changelog
The latest updates to Tinybird
Blog
Musings on transformations, tables and everything in between
Customer Stories
We help software teams ship features with massive data sets
Videos
Learn how to use Tinybird with our videos
Templates
Explore our collection of templates
Slack Community
Join our Slack community to get help and share your ideas
Back to columns
Scalable Analytics Architecture
Scalable Analytics Architecture
Jul 11, 2025
CI/CD with Tinybird Forward: Automating Real-Time Data Deployments
An example based on the Electric Project created in a previous post to show how to create a CI/CD workflow using Tinybird Forward.
Iago Enríquez
Data Engineer
1CI/CD with Tinybird Forward: Automating Real-Time Data Deployments
Scalable Analytics Architecture
Jun 27, 2025
Why we ditched Prometheus for autoscaling (and don't miss it)
Tinybird uses KEDA and its own real-time analytics platform to autoscale Kafka workloads. Learn how we made it work.
Víctor M. Fernández
Site Reliability Engineer
1Why we ditched Prometheus for autoscaling (and don't miss it)
Jun 27, 2025
We cut AWS costs by 20% while scaling faster with EKS, Karpenter, and Spot Instances
Scalable Analytics Architecture
Luis Rodríguez
Head of Infrastructure
1We cut AWS costs by 20% while scaling faster with EKS, Karpenter, and Spot Instances
Jun 27, 2025
Scaling up ClickHouse ingestion with a Multi-writer architecture
Scalable Analytics Architecture
Jordi Orihuela
Backend Engineer
1Scaling up ClickHouse ingestion with a Multi-writer architecture
Jun 27, 2025
How we protect your primary workloads with Compute-Compute Separation for Populates
Scalable Analytics Architecture
Jesús Botella
Backend Engineer
1How we protect your primary workloads with Compute-Compute Separation for Populates
Jun 27, 2025
How we made our ingestion pipeline 30% faster with C++ (not Rust, sorry)
Scalable Analytics Architecture
Javier Goizueta
Software Engineer
1How we made our ingestion pipeline 30% faster with C++ (not Rust, sorry)
Jun 27, 2025
How we automatically handle ClickHouse schema migrations
Scalable Analytics Architecture
Raquel Barbadillo
Software Engineer
1How we automatically handle ClickHouse schema migrations
Jun 03, 2025
Optimizing Apache Iceberg tables for real-time analytics
Scalable Analytics Architecture
Alberto Romeu
Backend Developer
1Optimizing Apache Iceberg tables for real-time analytics
May 23, 2025
Building Real-Time Analytics Applications with Redpanda, Iceberg, and Tinybird
Scalable Analytics Architecture
Alberto Romeu
Backend Developer
1Building Real-Time Analytics Applications with Redpanda, Iceberg, and Tinybird
May 20, 2025
Real-Time Analytics on Apache Iceberg with Tinybird
Scalable Analytics Architecture
Alberto Romeu
Backend Developer
1Real-Time Analytics on Apache Iceberg with Tinybird
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Apr 24, 2025
dbt in real-time
Scalable Analytics Architecture
Javier Santana
Co-founder
1dbt in real-time
Apr 21, 2025
How to count 100B events: Comparing architectures
Scalable Analytics Architecture
Ariel Pérez
Head of Product & Technology
1How to count 100B events: Comparing architectures
Apr 11, 2025
The simplest way to count 100B unique IDs: Part 2
Scalable Analytics Architecture
Ariel Pérez
Head of Product & Technology
1The simplest way to count 100B unique IDs: Part 2
Apr 08, 2025
Best practices for downsampling billions of rows of data
Scalable Analytics Architecture
Paco González
Data Engineer
1Best practices for downsampling billions of rows of data
Mar 07, 2025
How to run load tests in real-time data systems
Scalable Analytics Architecture
Ana Guerrero
Data Engineer
1How to run load tests in real-time data systems
Feb 21, 2025
The perfect data ingestion API design
Scalable Analytics Architecture
Javier Santana
Co-founder
1The perfect data ingestion API design
Feb 19, 2025
I've helped huge companies scale logs analysis. Here’s how.
Scalable Analytics Architecture
Paco González
Data Engineer
1I've helped huge companies scale logs analysis. Here’s how.
Dec 03, 2024
Building Real-Time Live Sports Viewer Analytics with Tinybird and AWS
Scalable Analytics Architecture
Ariel Pérez
Head of Product & Technology
1Building Real-Time Live Sports Viewer Analytics with Tinybird and AWS
Nov 06, 2024
Application Architecture: Combining DynamoDB and Tinybird
Scalable Analytics Architecture
Alasdair Brown
Developer Advocate
1Application Architecture: Combining DynamoDB and Tinybird
Oct 15, 2024
Simple patterns for aggregating on DynamoDB
Scalable Analytics Architecture
Cameron Archer
Head of Growth
1Simple patterns for aggregating on DynamoDB
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