Tinybird
The real-time data platform for building fast APIs on top of your data.
Tinybird is a data & databases tool built by Tinybird. It's best for Software teams building data-intensive applications and SaaS companies needing real-time dashboards. Pricing is contact. Main alternatives include Splunk.
Pricing
contact
Audience
Software teams building data-intensive applications
Community
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About Tinybird
Tinybird is a real-time data platform that enables developers to build fast APIs on top of their data. It provides the infrastructure and tooling needed to capture, store, transform, and serve data without dependencies on external tools or teams.
Tinybird is a data platform designed to help developers build real-time analytical features and APIs. It leverages ClickHouse, a high-performance OLAP database, and provides a developer-friendly experience for data ingestion, transformation, and API creation.
Key features include streaming ingestion, allowing for high-throughput data ingest from sources like Kafka, S3, and GCS. Tinybird offers a complete CLI for local development, schema iteration with safe migrations, and built-in observability. It also supports connecting to BI tools and ORMs.
Tinybird differentiates itself by offering ClickHouse performance with a Vercel-like developer experience. It aims to provide startup-level speed for enterprise-level data projects, enabling teams to ship faster and at a fraction of the cost. The platform is SOC 2 Type II certified, ensuring security and compliance for enterprise use.
Tinybird targets software teams that need to build data-intensive applications and features. It is particularly well-suited for use cases such as SaaS dashboards, observability platforms, AI analytics, crypto/finance applications, and real-time analytics. It empowers developers to build and scale data products without the complexities of managing underlying infrastructure.
Key Features
Pricing
contactContact sales for pricing information.
Who is it for?
Best for
- Building real-time analytics APIs
- Creating SaaS dashboards
- Developing observability platforms
- Implementing AI analytics
- Real-time data processing for crypto/finance
- Handling high-throughput streaming data
Not ideal for
- Simple data storage without analytical needs
- Projects with limited data volume or velocity
- Applications not requiring real-time data processing
- Teams without developer resources
Integrations
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