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Confluent Private Cloud (CPC) is a new software package that extends Confluent’s cloud-native innovations to your private infrastructure. CPC offers an enhanced broker with up to 10x higher throughput and a new Gateway that provides network isolation and central policy enforcement without client...
Confluent announces the General Availability of Queues for Kafka on Confluent Cloud and Confluent Platform with Apache Kafka 4.2. This production-ready feature brings native queue semantics to Kafka through KIP-932, enabling organizations to consolidate streaming and queuing infrastructure while...
Explore new Confluent Intelligence features: A2A integration, multivariate anomaly detection, vector search for Cosmos DB and S3 Vectors, Private Link, and MCP support.
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 […]
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 […]
The world is changing fast, and keeping up can be hard. Companies must evolve their IT to stay modern, providing services that are more and more sophisticated to their customers. […]
We are pleased to announce the release of ksqlDB 0.7.0. This release features highly available state, security enhancements for queries, a broadened range of language/data expressions, performance improvements, bug fixes, […]
We talked about how easy it is to send osquery logs to the Confluent Platform in part 1. Now, we’ll consume streams of osquery logs, detect anomalous behavior using machine […]
Apache Kafka® is often deployed alongside Elasticsearch to perform log exploration, metrics monitoring and alerting, data visualisation, and analytics. It is complementary to Elasticsearch but also overlaps in some ways, […]
When a company becomes overreliant on a centralized database, a world of bad things start to happen. Queries become slow, taxing an overburdened execution engine. Engineering decisions come to a […]
Now that we’ve learned about the processing layer of Apache Kafka® by looking at streams and tables, as well as the architecture of distributed processing with the Kafka Streams API […]
Part 2 of this series discussed in detail the storage layer of Apache Kafka: topics, partitions, and brokers, along with storage formats and event partitioning. Now that we have this […]
Part 1 of this series discussed the basic elements of an event streaming platform: events, streams, and tables. We also introduced the stream-table duality and learned why it is a […]
This four-part series explores the core fundamentals of Kafka’s storage and processing layers and how they interrelate. In this first part, we begin with an overview of events, streams, tables, […]
When KSQL was released, my first blog post about it showed how to use KSQL with Twitter data. Two years later, its successor ksqlDB was born, which we announced this […]
As a test class that allows you to test Kafka Streams logic, TopologyTestDriver is a lot faster than utilizing EmbeddedSingleNodeKafkaCluster and makes it possible to simulate different timing scenarios. Not […]
ksqlDB is a new kind of database purpose-built for stream processing apps, allowing users to build stream processing applications against data in Apache Kafka® and enhancing developer productivity. ksqlDB simplifies […]