What is Kafka Connect?

Question

Accepted Answer

**Kafka Connect** is a framework for **integrating Kafka with external systems** (databases, storage, services) — moving data in and out of Kafka without writing custom code, using reusable **connectors**. It simplifies building data pipelines.

## What Kafka Connect does

```text
KAFKA CONNECT → a framework for streaming data BETWEEN Kafka and external systems:
  → SOURCE connectors → pull data FROM external systems INTO Kafka (e.g. a database → Kafka)
  → SINK connectors → push data FROM Kafka TO external systems (e.g. Kafka → a data warehouse)
  → uses reusable CONNECTORS (pre-built integrations) instead of custom producer/consumer code
→ "plug in" connectors to integrate systems with Kafka
```

## Why use Kafka Connect

```text
✓ NO custom code → use existing connectors for common systems (databases, S3, Elasticsearch,
  data warehouses, etc.) instead of writing producers/consumers
✓ Reliable, scalable → handles offsets, retries, scaling, fault tolerance, distributed mode
✓ Standardized → consistent way to integrate; config-driven (declarative)
✓ Many connectors available (Confluent Hub, community) for common systems
```

## Common uses

```text
✓ DATA PIPELINES → stream data from databases into Kafka and out to other systems
✓ CHANGE DATA CAPTURE (CDC) → stream database changes into Kafka (e.g. Debezium) → react
  to data changes in real time
✓ INGESTION → bring data from many sources into Kafka
✓ EXPORT → move Kafka data to storage, search, analytics, warehouses
→ a key tool for building Kafka-based data integration/pipelines
```

## Why it matters

Understanding Kafka Connect is valuable because it's a **key tool for integrating Kafka with external systems**, central to building data pipelines, so it's useful knowledge for Kafka-based integration.

Kafka Connect addresses the common need to move data between Kafka and external systems (databases, storage, services) without writing custom integration code.

Understanding **what Kafka Connect does** — providing **source connectors** (pulling data from external systems into Kafka) and **sink connectors** (pushing data from Kafka to external systems), using reusable pre-built connectors instead of custom producer/consumer code — clarifies its role in data integration.

Understanding **why to use it** — avoiding custom code (using existing connectors for common systems like databases, S3, Elasticsearch, and data warehouses), reliability and scalability (handling offsets, retries, scaling, and fault tolerance in distributed mode), standardization (config-driven, declarative integration), and the availability of many connectors — clarifies its value over hand-writing integration code.

Understanding the **common uses** — data pipelines (streaming data between systems via Kafka), **change data capture** (streaming database changes into Kafka, e.g. with Debezium, to react to data changes in real time — an important pattern), ingestion (bringing data from many sources into Kafka), and export (moving Kafka data to storage, search, and analytics) — clarifies where Kafka Connect fits, especially for the data-pipeline and CDC use cases that are central to Kafka's role as a data backbone.

Kafka Connect significantly simplifies building Kafka-based data integration by providing reusable, reliable connectors.

Since Kafka Connect is a key tool for integrating Kafka with external systems (central to data pipelines and CDC) and understanding what it does, its benefits (no custom code, reliable, standardized), and its uses is useful for Kafka-based integration, understanding Kafka Connect is valuable, practically-relevant knowledge — a key tool for integrating Kafka with external systems via reusable connectors, central to building data pipelines and CDC, simplifying data integration, and important for Kafka's role as a data backbone connecting many systems.