Tinybird is a data platform that enables developers to ingest both batch and streaming data, query it using SQL, and publish APIs for user-facing analytics. By simplifying the creation of real-time data products, Tinybird addresses the challenge of rapidly delivering actionable insights from large datasets without the need for complex infrastructure management.
Funding
$30M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Building user-facing analytics requires significant engineering effort to ingest and transform data, manage complex infrastructure, and develop APIs that can deliver real-time insights. Traditional data warehouses and analytics tools often lack the speed and flexibility needed to power interactive, data-driven applications.
Solution
Tinybird is a data platform designed for building real-time, user-facing analytics. It allows developers to ingest both batch and streaming data, query it using SQL, and publish APIs for direct consumption by applications. Tinybird simplifies the process of creating data products by providing a managed infrastructure, a flexible SQL-based data transformation pipeline, and tools for API creation and authentication. This enables developers to rapidly deliver actionable insights from large datasets without the complexities of managing underlying infrastructure.
Target Audience
Tinybird's primary customers are developers and data teams building user-facing analytics, real-time dashboards, and data-driven applications across various industries, including gaming, web analytics, and e-commerce.
Features
- Blazing-fast ingestion of batch and streaming data
- Flexible SQL-based pipelines for data modeling and transformation
- API endpoint creation with OpenAPI specifications
- Authentication via static tokens or JWT for granular data access control
- Out-of-the-box embedded charts for data visualization
- CI/CD using a command-line interface (CLI) for automated deployments
- Production-ready observability with automatic performance and consumption data
- Data branching for experimentation and development
- Integrations with Apache Kafka, Confluent Cloud, Redpanda, Google BigQuery, Snowflake, and Amazon S3