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Stream Processing
Data Products, Data Contracts, and Change Data Capture
Change data capture is a popular method to connect database tables to data streams, but it comes with drawbacks. The next evolution of the CDC pattern, first-class data products, provide resilient pipelines that support both real-time and batch processing while isolating upstream systems...
Unlock Cost Savings with Freight Clusters–Now in General Availability
Confluent Cloud Freight clusters are now Generally Available on AWS. In this blog, learn how Freight clusters can save you up to 90% at GBps+ scale.
Contributing to Apache Kafka®: How to Write a KIP
Learn how to contribute to open source Apache Kafka by writing Kafka Improvement Proposals (KIPs) that solve problems and add features! Read on for real examples.
Announcing ksqlDB 0.10.0
We’re excited to announce the release of ksqlDB 0.10.0, available now in the standalone distribution and on Confluent Cloud! This version includes a first-class Java client, improved Apache Kafka® key […]
Unifying Streams and State: The Seamless Path to Real Time
More than ever before, people demand immediacy in every aspect of their lives. Expectations for how we shop, bank, and commute have completely evolved over the last decade. When you […]
Stream Processing with IoT Data: Challenges, Best Practices, and Techniques
The rise of IoT devices means that we have to collect, process, and analyze orders of magnitude more data than ever before. As sensors and devices become ever more ubiquitous, […]
Consistent Metastore Recovery for ksqlDB Using Apache Kafka Transactions
This is the second of a series of posts (part 1 | part 3) that dive deep into key improvements made to ksqlDB to prepare for production availability in Confluent […]
Building a Clickstream Dashboard Application with ksqlDB and Elasticsearch
Using a powerful, event-driven application can help you unlock insights contained in the event streams of your business. Before we get into the technology, let’s go over some questions you […]
Kafka Streams Interactive Queries Go Prime Time
What is stopping you from using Kafka Streams as your data layer for building applications? After all, it comes with fast, embedded RocksDB storage, takes care of redundancy for you, […]
Announcing ksqlDB 0.9.0
We’re pleased to announce the release of ksqlDB 0.9.0! This version includes support for multi-join statements, enhanced LIKE expressions, and a host of usability improvements. We’ll go through a few […]
From Eager to Smarter in Apache Kafka Consumer Rebalances
Everyone wants their infrastructure to be highly available, and ksqlDB is no different. But crucial properties like high availability don’t come without a thoughtful, rigorous design. We thought hard about […]
Highly Available, Fault-Tolerant Pull Queries in ksqlDB
One of the most critical aspects of any scale-out database is its availability to serve queries during partial failures. Business-critical applications require some measure of resilience to be able to […]
ksqlDB Execution Plans: Move Fast But Don’t Break Things
The ksqlDB Engineering Team has been hard at work preparing ksqlDB for production availability in Confluent Cloud. This is the first in a series of posts that deep dives into […]
Real-Time Data Replication with ksqlDB
Data can originate in a number of different sources—transactional databases, mobile applications, external integrations, one-time scripts, etc.—but eventually it has to be synchronized to a central data warehouse for analysis […]
ksqlDB: The Missing Link Between Real-Time Data and Big Data Streaming
Is event streaming or batch processing more efficient in data processing? Is an IoT system the same as a data analytics system, and a fast data system the same as […]
Announcing ksqlDB 0.8.0
The latest ksqlDB release introduces long-awaited features such as tunable retention and grace period for windowed aggregates, new built-in functions including LATEST_BY_OFFSET, a peek at the new server API under […]
Sharpening your Stream Processing Skills with Kafka Tutorials
Event stream processing solves many business challenges, from big data ingestion and data integration, to real-time data processing and IoT. It gives you the ability to analyze big data streams […]