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Connectors

Connect your data.
Keep your systems in sync.

Build pipelines across databases, messaging systems, cloud services and devices. Explore each integration’s role and release status before configuring your connection.

Explore connectors ↓Read the pipeline guide →
Database change captureEvent streamingCloud destinations
StreamSource integration hub connecting databases, cloud storage, devices, applications, analytics and APIs
Sources → Processing → Destinations
Integration framework

From source to destination.

A connector moves events between systems. A transform changes those events before the next system receives them.

01 / SOURCE

Bring events in.

Read database changes, subscribe to a message stream or receive device telemetry.

Examples: PostgreSQL CDC, MQTT, HTTP ingestBrowse sources →
02 / TRANSFORM

Make events useful.

Filter fields, normalize values, enrich records or apply your own processing logic.

Examples: Field mapper, Lookup enrich, Custom codeBrowse transforms →
03 / SINK

Keep systems current.

Write processed events to a database, warehouse, storage bucket or external API.

Examples: PostgreSQL, BigQuery, WebhookBrowse destinations →
Connector catalogue

Explore the connector catalogue.

Search a product, protocol or use case. Combine type and release-status filters to narrow the list.

Available · Listed as ready to useBeta · Validate for your workloadPlanned · Not available yet

Before you configure

Prepare your connection
for production.

Check these details for the integration you choose. Connection behavior, retries and delivery guarantees depend on the connector and destination.

See pipeline validation examples →
  1. Endpoint and access

    Confirm the address, credentials, TLS settings and network reachability.

  2. Event shape and topic

    Choose the input or output topic and validate required fields with a sample event.

  3. Retries and duplicate handling

    Test a repeated event and a temporary interruption before using production data.

Your custom integration

Extend the platform
with your own connector.

If your source isn’t in the catalogue, use a custom container to read or write Kafka events. Describe the configuration once and keep deployment consistent.

01Bring your container

Your protocol, your runtime.

02Define its configuration

Fields, credentials and topic mappings.

03Deploy with the pipeline

One workspace for built-in and custom logic.

Discuss your integration requirements.

Share your systems, data volumes and delivery requirements with our team.

Book a Demo →Try for Free