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Integrate MySQL with Kafka using the source MySQL Kafka connector
Quix enables you to publish data from MySQL to Apache Kafka and then process it. All of this in real time, using pure Python, and at any scale.
Move MySQL data to Kafka and process it in two simple steps
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Ingest data from MySQL into Kafka
Use the Quix-made MySQL Kafka source connector to publish data from MySQL into Quix-managed Apache Kafka topics. The MySQL connector enables you to stream data in a scalable, fault-tolerant manner, with consistently low latencies. This operation is facilitated through a straightforward connector configuration and supports JDBC compatible databases, making it easier to handle complex connector implementation.
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Process and transform data with Python
After data is ingested from MySQL, process and transform this streaming data on the fly with Quix Streams, an open-source, Kafka-based Python library. Quix Streams offers an intuitive Streaming DataFrame API (similar to pandas DataFrame) for real-time data processing. It supports aggregations, windowing, filtering, group-by operations, branching, merging, serialization, and more, allowing you to shape your data to fit your needs, including managing schema registry concerns and SQL queries customization.
Quix Kafka connectors — a simpler, better alternative to Kafka Connect
Quix offers a Python-native, developer-friendly approach to data integration that eliminates the complexity associated with Kafka Connect deployment, configuration, and management.
With Quix Kafka connectors, you can easily work with MySQL databases, without having to wrestle with complex connector configurations or managing MySQL driver dependencies.
Quix fully manages the entire Kafka connectors lifecycle, from deployment to monitoring. This means faster development, easier debugging, and lower operational overhead compared to traditional Kafka Connect implementations.
Quix, your solution to simplify real-time data integration
As a Kafka-based platform, Quix streamlines real-time data integration across your entire tech stack, empowering you to effortlessly collect data from disparate sources into Kafka, transform and process it with Python, and send it to your chosen destination(s).
By using Quix as your central data hub, you can:
- Accelerate time to insights from your data to drive informed business decisions
- Ensure data accuracy, quality, and consistency across your organization
- Automate data integration pipelines and eliminate manual SQL statements
- Manage and protect sensitive data with robust security measures
- Handle data from an entire table in a scalable, fault-tolerant way, with sub-second latencies, and exactly-once processing guarantees
- Reduce your data integration TCO to a fraction of the typical cost
- Benefit from managed data integration infrastructure, thus minimizing complexity and operational burden
- Use a flexible, comprehensive toolkit to build data integration pipelines, including CI/CD and IaC support, environment management features, observability and monitoring capabilities, an online code editor, Python code templates, a CLI tool, and 130+ Kafka source and sink connectors
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FAQs
What is MySQL?
MySQL is a popular open-source relational database management system that uses SQL for defining, manipulating, and querying data. It is known for its robustness, scalability, and ease of use. MySQL databases are frequently used for web applications, data warehousing, and e-commerce platforms, where reliable and efficient management of large data volumes is crucial. It supports various SQL queries and complex database operations.
What is Apache Kafka?
Apache Kafka is a scalable, reliable, and fault-tolerant event streaming platform that enables real-time integration and data exchange between different systems. Kafka’s publish-subscribe model ensures that any source system can write data to a central pipeline, while destination systems can read that data instantly as it arrives. In essence, Kafka acts as a central nervous system for streaming data. It helps organizations unify their data architecture and provide a continuous, real-time flow of information across disparate components.
What are Kafka connectors?
Kafka connectors are pre-built components that help integrate Apache Kafka with external systems. They allow you to reliably move data in and out of a Kafka cluster without writing custom integration code. There are two main types of Kafka connectors:
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Source connectors: These are used to pull data from source systems into Kafka topics.
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Sink connectors: These are used to push data from Kafka topics to destination systems.
What is real-time data, and why is it important?
Real-time data is information that’s made available for use as soon as it's generated. It’s passed from source to destination systems with minimal latency, enabling rapid decision-making, immediate insights, and instant actions. Real-time data is crucial for industries like finance, logistics, manufacturing, healthcare, game development, information technology, and e-commerce. It empowers businesses to improve operational efficiency, increase revenue, enhance customer satisfaction, quickly respond to changing conditions, and gain a competitive advantage.
What data can you publish from MySQL to Kafka in real time?
- Change data from your MySQL database, e.g., row insertions, updates, and deletions, along with relevant metadata
- SQL statements execution statistics, query performance metrics
- Table metadata including schema details, timestamp column information
- Transactional data, reflecting committed changes in MySQL tables
- User logs and audit trails with login details and activity logs
- Aggregated data results from complex queries on MySQL instance
- Event data tracking real-time application events mapped to specified tables
What are key factors to consider when publishing MySQL data to Kafka in real time?
- The connector begins by identifying the appropriate timestamp columns and uses the incrementing mode for capturing changes effectively.
- Managing database details and ensuring the connector configuration is aligned with the database timezone settings can present challenges.
- Transitioning connector implementation to handle different data formats requires thorough planning, especially when dealing with binary representation and schema variations.
- Properly setting up a MySQL connector configuration property ensures stable connectivity and data streaming between MySQL tables and Apache Kafka.
- The relational database’s performance considerations must be balanced while continually streaming large datasets to avoid degraded response times.
- Tailoring integration to comply with data governance, especially when data evolves, ensuring SQL queries maintain integrity and efficiency.
- Configuring MySQL driver settings for optimizing SQL queries to handle dynamic changes in database schemas.
How does the MySQL Kafka source connector offered by Quix work?
The MySQL Kafka source connector provided by Quix is fully managed and written in Python.
The connector continuously retrieves data from MySQL and publishes it to designated Quix-managed Kafka topics.
The connector provides strong data delivery guarantees (ordering and exactly-once semantics) to ensure data is reliably ingested into Kafka. You can customize its write performance and choose between several serialization formats (such as JSON, Avro, and Protobuf).
To find out more about the source MySQL Kafka connector offered by Quix, book a demo.
Does Quix offer a sink MySQL Kafka connector too?
Yes, Quix also provides a sink MySQL connector for Kafka.
In fact, Quix offers 130+ Kafka sink and source connectors, enabling you to move data from a variety of sources into Kafka, process it, and then send it to your desired destination(s). All in real time.