Airbyte CDK
Python SDK for building custom Airbyte connectors (sources and destinations). Provides base classes (AbstractSource, HttpStream, IncrementalMixin) that handle HTTP pagination, state management, schema inference, and retry logic. Custom connectors built with CDK run in Docker containers and integrate with Airbyte's orchestration layer. Used to connect custom APIs or proprietary data sources to Airbyte's connector catalog.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Credentials handled via Airbyte's secret management. Connectors run in isolated Docker containers. Source credentials never leave the connector's execution context.
⚡ Reliability
Best When
You need to build a reusable connector for a data source that isn't in Airbyte's catalog and want to use Airbyte's orchestration, monitoring, and scheduling infrastructure.
Avoid When
You don't use Airbyte, need one-time data extracts, or need real-time streaming — CDK connectors are batch-sync focused.
Use Cases
- • Build custom Airbyte source connectors for internal APIs or proprietary data sources not in Airbyte's catalog
- • Create Airbyte destination connectors for custom data warehouses or streaming services
- • Implement incremental sync (cursor-based) for custom data sources to reduce API calls in recurring syncs
- • Publish custom connectors to Airbyte's open-source connector registry for community use
- • Build agent data ingestion pipelines where agent outputs need to flow into data warehouses via Airbyte
Not For
- • Teams without Airbyte infrastructure — CDK connectors only run within Airbyte's orchestration system
- • One-time data migrations — CDK is for recurring sync connectors; use dbt or custom scripts for one-time migrations
- • Real-time streaming — Airbyte is batch-oriented; use Kafka or Flink for real-time streaming
Interface
Authentication
SDK library. Source/destination auth is implemented within the connector using Airbyte's spec/config pattern.
Pricing
MIT license. Part of the Airbyte open source project.
Agent Metadata
Known Gotchas
- ⚠ CDK connectors run in Docker containers — local testing requires Docker and the Airbyte connector runner; development feedback loop is slower than pure Python testing
- ⚠ Schema inference vs. explicit schema definition — HttpStream can infer JSON schema but inferred schemas may change unexpectedly; explicit catalog specs are more reliable
- ⚠ Incremental sync requires implementing get_updated_state() — incorrect state management causes either duplicate data or missed records on subsequent syncs
- ⚠ HTTP rate limiting must be implemented in the connector — CDK's HttpStream handles retry but the rate limit strategy must match the source API's limits
- ⚠ Connector spec (config JSON schema) must match exactly what the source expects — mismatches cause authentication failures that are hard to debug without direct API access
- ⚠ CDK versions update frequently with deprecation cycles — pin CDK version and test upgrade paths; some CDK releases have breaking changes to base class APIs
Alternatives
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Scores are editorial opinions as of 2026-03-07.