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Getting Started with the Kafka Connect for YugabyteDB (beta)

Kafka Connect is a popular tool for scaling and reliably streaming data between Apache Kafka and other data systems. It ships with a JDBC Sink which is used to insert data from Kafka to a database. Although the default JDBC Sink is good for many popular RDBMS it isn’t optimized for distributed SQL databases that provide linear scalability and high availability like YugabyteDB.

In our earlier blog introducing YugabyteDB 2.7,

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Announcing the Kafka Connect YugabyteDB Sink Connector

For customers that run Kafka for their streaming data platform, the Kafka Connect Sink plugin handles delivery of specific topic data to a YugabyteDB instance. As soon as new messages are published, the Sink manages forwarding and automatic addition to a destination table.

YugabyteDB is a high-performance, distributed SQL database built on a scalable and fault-tolerant design inspired by Google Spanner. Yugabyte’s SQL API (YSQL) supports most of PostgreSQL’s functionality and is wire-protocol compatible with PostgreSQL drivers.

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Best Practices for Deploying Confluent Kafka, Spring Boot & Distributed SQL Based Streaming Apps on Kubernetes

In our previous post “Develop IoT Apps with Confluent Kafka, KSQL, Spring Boot & Distributed SQL”, we highlighted how Confluent Kafka, KSQL, Spring Boot and YugabyteDB can be integrated to develop an application responsible for managing Internet-of-Things (IoT) sensor data. In this post, we will review the challenges and best practices associated with deploying such a stateful streaming application on Kubernetes.

Challenges of Streaming Apps

Streaming apps are inherently stateful in nature given the large volume of data managed and that too continuously.

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Develop IoT Apps with Confluent Kafka, KSQL, Spring Boot & Distributed SQL

In our previous post “5 Reasons Why Apache Kafka Needs a Distributed SQL Database”, we highlighted why Kafka-based data services need a distributed SQL database like YugabyteDB as their highly scalable, long-term persistent data store. In this post, we show how Confluent Kafka, KSQL, Spring Boot and YugabyteDB can be integrated to develop an application for managing Internet-of-Things (IoT) sensor data.

The Scenario – IoT-Enabled Fleet Management

A trucking company wants to track its fleet of IoT-enabled vehicles that are delivering shipments across the country.

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5 Reasons Why Apache Kafka Needs a Distributed SQL Database

Modern enterprise applications must be super-elastic, adaptable, and running 24/7. However, traditional request-driven architectures entail a tight coupling of applications. For example, App 1 asks for some information from App 2 and waits. App 2 then sends the requested information to App 1. This sort of app-to-app coupling hinders development agility and blocks rapid scaling.

In event-driven architectures, applications publish events to a message broker asynchronously. They trust the broker to route the message to the right application,

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