Based on a report, Apache Kafka stores and streams more than 7 trillion real-time messages per day. However, fetching real-time messages from external sources or applications is a tedious process as it involves writing extensive code for implementing the data exchange. To eradicate such complexities, you can use database connecting tools like Debezium and Kafka Connect for continuously monitoring and streaming real-time data from external database systems. When it comes to choosing the appropriate database connecting tool, the decision of Debezium vs Kafka Connect is a relatively tough one.
Both Debezium and Kafka Connect platforms are built on top of the Kafka ecosystem to facilitate data exchange between Kafka servers and the respective external database applications. In this article, you will learn about Debezium, Kafka Connect, and the fundamental differences between Debezium and Kafka Connect platforms.
Prerequisites
- Fundamental understanding of databases and real-time event streaming.
Understanding Debezium
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Originally developed by Red Hat, Debezium is an open-source and distributed data monitoring platform that continuously captures and streams real-time modifications made on external database systems. In other words, Debezium is a low latency data streaming platform that is developed mainly to implement the CDC (Change Data Capture) operation. With CDC operation, Debezium converts external databases into real-time event streams, enabling you to fetch and record row-level changes made on the respective database applications.
Since Debezium is built on top of the Kafka environment, it captures and stores every real-time message stream in Kafka topics present inside Kafka servers. In addition, Debezium consists of various database connectors that allow you to connect and capture real-time updates from external database applications like MySQL, Oracle, and PostgreSQL. For example, Debezium’s MySQL connector fetches real-time updates from the MySQL database, while Debezium’s PostgreSQL connector will capture data change from the PostgreSQL database.
Key Features of Debezium
- CDC: The primary use case of Debezium is to implement CDC (Change Data Capture), which allows you to capture and stream real-time data modifications made on external databases. With CDC operation, you can record and stream every data change made on databases according to the row-level manipulation techniques like insert, delete, and update.
- Data monitoring: Debezium is capable of continuously monitoring, capturing, and streaming row-level modifications made on external database systems such as MySQL, PostgreSQL, and SQL Server. It turns such external databases into event streams, thereby allowing database-synchronized downstream applications to respond and act with respect to the row-level changes made on database applications.
- Data consistency: Since Debezium collects and saves data in log-based CDC format, every real-time data modification or update made on the database is reliably kept and structured in a precise sequence inside the commit log.
- Fault-tolerant: Since Debezium is a distributed platform, the application’s architecture is designed to be fault-tolerant and flexible even when any faults or failures occur during the continuous data transfer. The real-time event changes are replicated, stored, and distributed across multiple machines, thereby decreasing the risk of information loss.
- Data Integration: Debezium can connect with various external database applications to continuously monitor and capture row-level changes made on the respective database. It has a vast set of database connectors like MySQL and Oracle connectors, which embed with the respective database to capture and stream real-time changes.
Understanding Kafka Connect
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Kafka Connect is a distributed platform that allows you to share and stream real-time data between Apache Kafka environment and external applications. It is a highly scalable and reliable service that makes real-time messages always available even if one of the servers fails in the Kafka ecosystem, making it an exceptional fault tolerance solution. Furthermore, Kafka Connect consists of various JDBC (Java Database Connectivity) connectors that allow you to establish connections between Kafka servers and external applications like Amazon S3, Amazon Kinesis, Apache Cassandra, MongoDB, and Hadoop.
Key Features of Kafka Connect
- Flexibility: Since Kafka Connect is a distributed architecture with greater scalability and reliability, it is highly flexible when it comes to synchronizing the Kafka environment with other external applications.
- Data Sharing: Kafka Connect platform provides you with a vast set of pluggable components that allows you to embed or integrate with other external applications to facilitate the process of data exchange. In other words, with the Kafka Connect platform, you can easily share real-time data between the Kafka ecosystem and other applications to implement the continuous streaming process.
- Connectors: Kafka Connect has two types of connectors, such as source connectors and sink connectors. The source connector allows you to import or ingest data from external sources into Kafka servers, while sink connectors enable you to distribute or export data from Kafka servers to other downstream applications.
- REST APIs: Kafka Connect provides you with various REST APIs with different functionalities for managing the connectors in the Kafka cluster. With REST APIs, you can easily subscribe and publish to Kafka topics for writing and fetching real-time messages to and fro the Kafka servers. Using Kafka Connect’s REST APIs, you can eliminate the need for deploying intermediate data connectors for implementing data exchange operations.
Factors that Drive the Debezium vs Kafka Connect Decision
Now that you have a basic idea of both concepts, let us attempt to answer the Debezium vs Kafka Connect question of how to make a decision between the two. There is no one-size-fits-all answer here and the decision has to be taken based on the business requirements and parameters listed below. The following are the key factors that drive the Debezium vs Kafka Connect decision:
1. Architecture
A) Debezium Architecture
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The Debezium architecture mainly comprises three components, such as external source databases, Debezium Server, and downstream applications like Redis, Amazon Kinesis, Pulsar, and Google Pub/Sub. Debezium server acts as a mediator to capture and stream real-time data change between external databases and consumer applications. The above-shown diagram is a simplified architecture of the Debezium platform. However, the end-to-end data capture pipeline using the Debezium platform is given below.
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The source connectors of Debezium monitor and capture real-time data updates from external database systems such as MySQL and PostgreSQL, as shown in the above image. The captured real-time updates are stored in Kafka topics present inside the Kafka servers. Inside Kafka topics, the captured updates are stored in the form of a commit log, which perfectly manages and organizes the messages one after another in sequential order, thereby enabling consumers to fetch data updates based on the modification order. Consequently, the change event records present inside Kafka topics are fetched by the external or downstream applications using the sink connectors such as JDBC and ElasticSearch connector.
B) Kafka Connect Architecture
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The Kafka Connect architecture mainly has three components, namely Kafka Connect Cluster, external source database, and external sink database. As shown in the above architecture diagram, the Kafka Connect Cluster has two Kafka connectors: Source connectors and sink connectors. The source connectors of the Kafka connect platform fetch real-time messages from external source applications, whereas sink connectors distribute records to external or downstream consumer applications.
2. Scalability
Debezium and Kafka Connect are effectively the same when it comes to scalability. In addition, since Debezium and Kafka connect platforms are distributed, the workloads are distributed and balanced across multiple systems, resulting in greater stability and fault tolerance. The real-time data will be secure within other servers or systems if one of the machines crashes or fails, making the data streaming service extremely fault resistant.
With the scalable and fault-tolerant feature, streaming platforms like Debezium and Kafka Connect can ensure that all connectors and servers continually function without any bottlenecks or disruptions. However, Kafka Connect is slightly more scalable than Debezium since it is capable of implementing end-to-end data exchange between producer and downstream applications by utilizing JDBC source and sink connectors, respectively.
3. Use Cases
Debezium platform has a vast set of CDC connectors, while Kafka Connect comprises various JDBC connectors to interact with external or downstream applications. However, Debeziums CDC connectors can only be used as a source connector that captures real-time event change records from external database systems. In contrast, Kafka Connect’s JDBC connectors can act as the source and sink connectors for distributing and fetching data changes to and fro the database applications that support the JDBC driver.
In Kafka Connect, the JDBC source connector imports or reads real-time messages from any external data source, while the JDBC sink connector distributes real-time records across multiple consumer applications. Furthermore, JDBC connectors do not capture and stream deleted records, whereas CDC connectors are capable of streaming all real-time updates, including deleted entries. Moreover, JDBC connections always query database updates at certain and predetermined intervals, while CDC connectors regularly record and transmit real-time event changes as soon as they occur on the respective database systems.
Conclusion
This article gave a comprehensive analysis of the 2 popular Database Connecting tools in the market today Debezium vs Kafka Connect. Even though 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 distinctions. Based on your use cases and business requirements, you can make the decision of Debezium vs Kafka Connect platforms for monitoring and tracking updates made on external or third-party applications. However, in businesses, extracting complex data from a diverse set of Data Sources can be a challenging task and this is where Hevo saves the day!
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Ishwarya is a skilled technical writer with over 5 years of experience. She has extensive experience working with B2B SaaS companies in the data industry, she channels her passion for data science into producing informative content that helps individuals understand the complexities of data integration and analysis.
