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Tags: Schema Registry
Data Sharing Patterns with Confluent Schema Registry
Sharing metadata on the data you store in your Confluent cluster is paramount to allow for effective sharing of that data across the enterprise. As the usage of real-time data […]
Easily Copy or Migrate Schemas Anywhere with Schema Linking
Schema Linking is a new feature that’s available in preview for both Confluent Cloud and Confluent Platform 7.0 and can be used to complement Cluster Linking, in order to keep […]
Using kafka-merge-purge to Deal with Failure in an Event-Driven System at FLYERALARM
Failures are inevitable in any system, and there are various options for mitigating them automatically. This is made possible by event-driven applications leveraging Apache Kafka® and built with fault tolerance […]
Keys in ksqlDB, Unlocked
One of the most highly requested enhancements to ksqlDB is here! Apache Kafka® messages may contain data in message keys as well as message values. Until now, ksqlDB could only […]
How to Consume Data from Apache Kafka Topics and Schema Registry with Confluent and Azure Databricks
How do you process IoT data, change data capture (CDC) data, or streaming data from sensors, applications, and sources in real time? Apache Kafka® and Apache Spark® are widely adopted […]
8 Years of Event Streaming with Apache Kafka
Since I first started using Apache Kafka® eight years ago, I went from being a student who had just heard about event streaming to contributing to the transformational, company-wide event […]
Powering Microservices at SEI Investments with Event Streaming
We launched a transformation initiative three years ago that transitioned SEI Investments from a monolithic database-oriented architecture to a containerized services platform with an event-driven architecture based on Confluent Platform. […]
Ensure Data Quality and Data Evolvability with a Secured Schema Registry
Organizations define standards and policies around the usage of data to ensure the following: Data quality: Data streams follow the defined data standards as represented in schemas Data evolvability: Schemas […]
Analysing Historical and Live Data with ksqlDB and Elastic Cloud
Building data pipelines isn’t always straightforward. The gap between the shiny “hello world” examples of demos and the gritty reality of messy data and imperfect formats is sometimes all too […]
Use Cases and Architectures for HTTP and REST APIs with Apache Kafka
This blog post presents the use cases and architectures of REST APIs and Confluent REST Proxy, and explores a new management API and improved integrations into Confluent Server and Confluent […]
Self-Describing Events and How They Reduce Code in Your Processors
Have you ever had to write a program that needed to handle any data payload that could be thrown at you? If so, did you always have to update the […]
How to Choose Between Strict and Dynamic Schemas
Event modeling has always been a pain point in organizations. From figuring out the standard format of your schemas, processing said data models effectively, and finally testing before you deploy […]
Building Streaming Data Architectures with Qlik Replicate and Apache Kafka
A fundamental challenge with today’s “data explosion” is finding the best answer to the question, “So where do I put my data?” while avoiding the longer-term problem of data warehouses, […]
ksqlDB Meets Java: An IoT-Inspired Demo of the Java Client for ksqlDB
Stream processing applications, including streaming ETL pipelines, materialized caches, and event-driven microservices, are made easy with ksqlDB. Until recently, your options for interacting with ksqlDB were limited to its command-line […]