Stream data from GitHub to Tinybird
Move data from GitHub to Tinybird in minutes using Estuary. Stream, batch, or continuously sync data with control over latency from sub-second to batch.
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- 200+Of connectors
- 5500+Active users
- <100msEnd-to-end latency
- 7+GB/secSingle dataflow
How to integrate GitHub with Tinybird in 3 simple steps
Connect GitHub as your data source
Set up a source connector for GitHub in minutes. Estuary supports streaming (including CDC where available) and batch data capture through events, incremental syncs, or snapshots — without custom pipelines, agents, or manual configuration.
Configure Tinybird as your destination connector
Estuary supports intelligent schema handling, with schema inference and evolution tools that help align source and destination structures over time. It supports both batch and streaming data movement, reliably delivering data to Tinybird.
Deploy and Monitor Your End-to-End Data Pipeline
Launch your pipeline and monitor it from a single UI. Estuary guarantees exactly-once delivery, handles backfills and replays, and scales with your data — without engineering overhead.

GitHub connector details
The GitHub connector continuously captures repository and organization data from GitHub into Estuary collections using the GitHub REST API, enabling right-time visibility across code, collaboration, and DevOps activities.
- Comprehensive coverage: Captures a wide range of GitHub resources including commits, pull requests, issues, workflows, releases, stargazers, and more, spanning both batch and incremental data.
- Right-time synchronization: Continuously ingests new commits, issues, and discussions as they occur, providing developers and data teams with an up-to-date view of repository activity.
- Flexible authentication: Supports OAuth2 for secure browser-based access or Personal Access Tokens (PATs) for command-line or managed integration setups.
- Granular configuration: Allows selective repository capture, branch-level filtering, and adjustable page sizes for large projects.
- Scalable for enterprise teams: Efficiently handles multi-repository or organization-wide synchronization while respecting GitHub API rate limits.
- Schema-aligned structure: Each GitHub resource maps to a separate Flow collection, simplifying downstream analysis, metrics tracking, or data lake ingestion.
💡 Tip: For organizations with many repositories, use wildcard patterns (like org/*) to automatically capture all repositories under one organization, ensuring comprehensive and future-proof coverage of your GitHub data.

Tinybird connector details
Real-time analytics in Tinybird start with live data — and Estuary makes that possible. By using the Tinybird variant of the Dekaf connector, you can stream data from Estuary collections directly into Tinybird as Kafka-compatible messages. This gives you a continuous, low-latency data feed for powering dashboards, APIs, and user-facing analytics.
- Instant data delivery: Estuary publishes updates and inserts in real time to Tinybird via Avro-encoded Kafka topics
- Effortless authentication: Connect using your Estuary materialization name as the username and your auth token as the password
- Flexible workspace setup: Works seamlessly with both Tinybird Forward (CLI-based) and Tinybird Classic (UI-based) environments
- Schema-aware integration: Includes an Avro schema registry endpoint that Tinybird can automatically decode
- Custom deletion handling: Choose between kafka (null-value deletes) or cdc (explicit deletion records) modes for soft or hard delete logic
- Optimized for analytics: Configure Tinybird datasources using MergeTree or ReplacingMergeTree engines for deduplication and efficient querying
💡 Tip: When using CDC deletion mode, extract the _is_deleted field and apply the FINAL keyword in Tinybird queries to automatically filter out deleted rows.
Estuary in action
See how to build end-to-end pipelines using no-code connectors in minutes. Estuary does the rest.
Spend 2-5x less
Estuary customers not only do 4x more. They also spend 2-5x less on ETL and ELT. Estuary's unique ability to mix and match streaming and batch loading has also helped customers save as much as 40% on data warehouse compute costs.

GitHub to Tinybird pricing estimate
Estimated monthly cost to move 800 GB from GitHub to Tinybird is approximately $1,000.
Data moved
Choose how much data you want to move from GitHub to Tinybird each month.
GB
Choose number of sources and destinations.
Why pay more?
Move the same data for a fraction of the cost.



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Frequently Asked Questions
Is this integration suitable for production workloads?
Yes. Estuary pipelines are designed for production use, with exactly-once delivery semantics, automated backfills, and continuous operation at scale.
Can I control where my data runs and is processed?
Yes. Estuary offers multiple deployment options, including fully managed SaaS, private deployments, and bring-your-own-cloud (BYOC). This allows teams to control where their data plane runs and meet security, compliance, and networking requirements. Learn more about Estuary's security and deployment options.
Can I build this GitHub to Tinybird integration manually?
Yes, it's possible to build a manual pipeline using custom scripts, scheduled jobs, or open-source tools. However, manual approaches typically require ongoing maintenance, custom error handling, schema management, and operational overhead. Estuary simplifies this by providing a managed pipeline with built-in reliability, scaling, and monitoring.
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