Debezium vs Kafka Connect Simplified: 3 Key Differences (2023)

Based onMessage, stores and transmits Apache Kafka7 billionNews in real time per day. However, retrieving feeds from external sources or applications is a tedious process due to the need to write extensive code to implement the data exchange. To eliminate such complexities, you can use database connection tools like Debezium and Kafka Connect to continuously monitor and stream real-time data from external database systems. When selecting the right database connection tool, the decision is up to you.Connection Debezium x Kafkait is relatively difficult.


The Debezium and Kafka Connect platforms build on the Kafka ecosystem to facilitate data exchange between Kafka servers and their respective external database applications. In this article, you will learn more about Debezium, Kafka Connect, and the fundamental differences between the Debezium and Kafka Connect platforms.

(Video) Stream your PostgreSQL changes into Kafka with Debezium


  • requirements
  • understand ten
  • Key features of Debezium
  • Comprender Kafka Connect
  • Kafka Connect main features
  • Factors that led to the decision between Debezium and Kafka Connect
    • Debezius frente a Kafka Connect: Architektur
    • Debezium vs Kafka Connect: Scalability
    • Debezium vs Kafka Connect: Use Cases
  • Diploma


  • Basic understanding of databases and real-time event streaming.

understand ten

Debezium vs Kafka Connect Simplified: 3 Key Differences (1)

Originally developed by Red Hat, Debezium is an open source distributed data monitoring platform that continuously captures and transmits changes to external database systems in real time. In other words, Debezium is a low latency data transmission platform designed primarily to implement CDC (Change Data Capture) operations. With the CDC operation, Debezium transforms external databases into real-time event streams, allowing you to retrieve and log row-level changes made in the respective database applications.

Because Debezium is based on the Kafka environment, it captures and stores all real-time message flows in the Kafka threads that exist on the Kafka servers. In addition, Debezium consists of several database connectors that allow you to connect to and collect real-time updates from external database applications such as MySQL, Oracle, and PostgreSQL. For example, the Debezium MySQL connector pulls real-time updates from the MySQL database, while the Debezium PostgreSQL connector captures changing data from the PostgreSQL database.

Key features of Debezium

  • CENTERS FOR DISEASE CONTROL AND PREVENTION:The main use case for Debezium is the implementation of CDC (Change Data Capture), which allows you to capture and transmit real-time data changes made to external databases. The CDC operation allows you to record and broadcast all data changes made to databases based on row-level manipulation techniques such as insert, delete, and update.
  • Data monitoring:Debezium can continuously monitor, capture, and push row-level changes made to external database systems such as MySQL, PostgreSQL, and SQL Server. It turns these external databases into event streams, allowing downstream applications that are in sync with the database to react and respond to row-level changes made in database applications.
  • Data consistency:Because Debezium collects and stores data in record-based CDC format, every real-time data update or change made to the database is reliably maintained and structured in a precise order within the commit record.
  • Fault tolerance:Because Debezium is a distributed platform, the application architecture is designed to be fault tolerant and resilient even when crashes or crashes occur during continuous data transfer. Real-time event changes are replicated, stored, and distributed across multiple computers, reducing the risk of information loss.
  • Data integration:Debezium can connect to various external database applications to continuously monitor and capture row level changes made to the respective database. It has a variety of database connectors like MySQL and Oracle connectors that integrate with the respective database to capture and stream changes in real time.

Comprender Kafka Connect

Debezium vs Kafka Connect Simplified: 3 Key Differences (2)

Kafka Connect is a distributed platform that allows you to exchange and stream data in real time between the Apache Kafka environment and external applications. It is a highly scalable and reliable service that always delivers messages in real time, even if one of the servers in the Kafka ecosystem fails, making it an exceptional fault-tolerance solution. In addition, Kafka Connect consists of several Java Database Connectivity (JDBC) connectors that enable connections between Kafka servers and external applications such as Amazon S3, Amazon Kinesis, Apache Cassandra, MongoDB, and Hadoop.

Kafka Connect main features

  • flexibility: Being a distributed architecture with greater scalability and reliability, Kafka Connect is very flexible when it comes to synchronizing the Kafka environment with other external applications.
  • Data transfer:The Kafka Connect platform offers a wide range of interchangeable components that allow you to embed or integrate other external applications to facilitate the data exchange process. In other words, with the Kafka Connect platform, you can easily exchange real-time data between the Kafka ecosystem and other applications to implement the streaming process.
  • Connections:Kafka Connect has two types of connectors, e.g. B. Source connectors and sink connectors. The source connector allows you to import or ingest data from external sources into the Kafka servers, while the destination connectors allow you to distribute or export data from the Kafka servers to other downstream applications.
  • REST API:Kafka Connect provides several REST APIs with different functions to manage connectors in the Kafka cluster. With REST APIs, you can easily subscribe to and publish to Kafka topics to write and retrieve messages in real time on Kafka servers. With Kafka Connect REST APIs, you can eliminate the need to provide intermediate data connectors to implement data exchange operations.

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(Video) Apache Kafka and Debezium | DevNation Tech Talk

Factors that led to the decision between Debezium and Kafka Connect

Now that you have a basic idea of ​​both concepts, let's try to answer the Debezium vs Kafka Connect question on how to make a decision between the two. There is no one-size-fits-all answer, and the decision should be made based on the needs and business parameters listed below. Below are the main factors that influenced the decision between Debezium and Kafka Connect:

(Video) Apache Kafka® 101: Kafka Connect

  • Debezius frente a Kafka Connect: Architektur
  • Debezium vs Kafka Connect: Scalability
  • Debezium vs Kafka Connect: Use Cases

1. Debezium frente a Kafka Connect: Architektur

A) Debezium Architecture

Debezium vs Kafka Connect Simplified: 3 Key Differences (3)

The Debezium architecture mainly consists of three components such as external source databases, Debezium server, and downstream applications like Redis, Amazon Kinesis, Pulsar, and Google Pub/Sub. The Debezium server acts as an intermediary to capture and transmit data changes in real time between external databases and consumer applications. The diagram shown above is a simplified architecture of the Debezium platform. However, the end-to-end data ingestion pipeline using the Debezium platform is provided below.

Debezium vs Kafka Connect Simplified: 3 Key Differences (4)

Debezium's source connectors monitor and collect real-time data updates from external database systems, such as MySQL and PostgreSQL, as shown in the image above. Captured real-time updates are stored in Kafka topics that reside on Kafka servers. Kafka threads store captured updates in the form of a commit record, which manages and arranges messages one at a time in sequential order, allowing consumers to retrieve data updates based on the changed order. Consequently, change event logs present in Kafka topics are retrieved from external or downstream applications using sink connectors, such as the JDBC connector and ElasticSearch.

B) Arquitectura de Kafka Connect

Debezium vs Kafka Connect Simplified: 3 Key Differences (5)

The architecture of Kafka Connect mainly consists of three components, viz. h Kafka Connect cluster, external source database, and external sink database. As shown in the architecture diagram above, the Kafka Connect cluster has two Kafka connectors: source connectors and sink connectors. Kafka Connection Platform source connectors pull messages in real time from external source applications, while destination connectors distribute logs to external or downstream consuming applications.

2. Debezium vs. Kafka Connect: Scalability

Debezium and Kafka Connect are pretty much the same when it comes to scalability. Additionally, since the Debezium and Kafka plug-in platforms are distributed, workloads are distributed and balanced across multiple systems, resulting in greater stability and fault tolerance. Real-time data is safe on other servers or systems if one of the machines fails or crashes, making the data streaming service extremely resilient to failures.

With the scalable and fault-tolerant feature, streaming platforms like Debezium and Kafka Connect can ensure all connectors and servers run continuously without bottlenecks or outages. However, Kafka Connect is slightly more scalable than Debezium, as it is capable of implementing end-to-end data exchange between producer and downstream applications using JDBC sink and source connectors, respectively.

(Video) Data Pipelines: Using CDC to Ingest Data into Kafka

3. Debezium vs Kafka Connect: Use Cases

The Debezium platform has a variety of CDC connectors, while Kafka Connect includes multiple JDBC connectors for interfacing with external or downstream applications. However, Debezium's CDC connectors can only be used as a source connector, capturing real-time event changelogs from external database systems. On the other hand, Kafka Connect JDBC connectors can act as source and sink connectors to distribute and get data changes from JDBC driver compliant database applications.

In Kafka Connect, the source JDBC connector imports or reads messages from any external data source in real time, while the sink JDBC connector distributes records to various consuming applications in real time. Also, JDBC connectors do not collect or stream deleted records, whereas CDC connectors can stream all updates in real time, including deleted entries. Furthermore, JDBC connectors always poll for database updates at fixed, predetermined intervals, while CDC connectors regularly record and broadcast event changes in real time as they occur in the respective database systems.


This article provides a complete overview of the 2 popular database connection tools on the market today Debezium vs. Kafka Connect. Although Debezium and Kafka Connect are distributed platforms that allow you to integrate and interact with external database systems to implement data exchange, they also have certain differences. Depending on your use cases and business needs, you may decide to use the Debezium or Kafka Connect platforms to monitor and track updates from third-party or external applications. However, in business, extracting complex data from a variety of data sources can be a challenging task, and that's where Hevo saves the day!

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(Video) Debezium & Kafka Change Data Capture

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Let us know about your experience of learning about Debezium vs Kafka Connect in the comments below!


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4. Migrating Legacy Data to FHIR at scale - ETL using Kafka, Debezium, and Nifi
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5. Run Debezium Kafka Connect using Docker | Kafka | Zookeeper | Kafdrop | Docker Compose | Part-6
6. Data Pipelines: Ingest Data From MySQL Into Kafka with Kafka Connect (Hands On)


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