Systems | Development | Analytics | API | Testing

New with Confluent Platform: Enhanced security with OAuth Support, Confluent Platform for Apache Flink (LA), a new HTTP Source Connector, and More

At Confluent we’re committed to building the world's leading data streaming platform that's cloud-native, complete, and available everywhere your data and applications reside. We offer this data streaming platform as a fully managed service in the cloud—Confluent Cloud; as a self-managed software that runs in your own environments—Confluent Platform; or as a hybrid of each of these.

Flink AI: Real-Time ML and GenAI Enrichment of Streaming Data with Flink SQL on Confluent Cloud

Modern data platforms enable enterprises to extract valuable business insights from data, sourced from various origins. Data engineers, data scientists, and other data practitioners utilize both data streaming and batch processing frameworks as a means to provide these insights. While batch processes work on historical data, stream processing extracts insights in real time, enabling businesses to react faster with respect to changing events.

Introducing Apache Kafka 3.8

We are proud to announce the release of Apache Kafka 3.8.0. This release contains many new features and improvements. This blog post will highlight some of the more prominent features. For a full list of changes, be sure to check the release notes. See the Upgrading to 3.8.0 from any version 0.8.x through 3.7.x section in the documentation for the list of notable changes and detailed upgrade steps. In a previous release, 3.6, Tiered Storage was released as early access feature.

Accelerate your data streaming journey with the latest in Confluent Cloud

The Q2 2024 Confluent Cloud launch introduces a suite of enhancements across the four key pillars of a Data Streaming Platform - Stream, Connect, Process, and Govern – alongside some significant work we have been doing with our partner ecosystem to help customers unlock new possibilities. Confluent has helped over 4,900+ global enterprises start their data streaming journey and was recently named a Leader by Forrester Research in The Forrester Wave: Streaming Data Platforms, Q4 2023.

Building a Full-Stack Application With Kafka and Node.js

A well-known debate: tabs or spaces? Sure, we could set up a Google Form to collect this data, but where’s the fun in that? Let’s settle the debate, Kafka-style. We’ll use the new confluent-kafka-javascript client (not in general availability yet) to build an app that produces the current state of the vote counts to a Kafka topic and consumes from that same topic to surface them to a JavaScript frontend.

MiFID II: Data Streaming for Post-Trade Reporting

The Markets in Financial Instruments Directive II (MiFID II) came into effect in January 2018, aiming to improve the competitiveness and transparency of European financial markets. As part of this, financial institutions are obligated to report details of trades and transactions (both equity and non-equity) to regulators within certain time limits.

How to Scale RAG and Build More Accurate LLMs

This article was originally published on The New Stack on June 10, 2024. Retrieval augmented generation (RAG) has emerged as a leading pattern to combat hallucinations and other inaccuracies that affect large language model content generation. However, RAG needs the right data architecture around it to scale effectively and efficiently.

Unlocking the Edge: Data Streaming Goes Where You Go with Confluent

While cloud computing adoption continues to accelerate due to its tremendous value, it has also become clear that edge computing is better suited for a variety of use cases. Organizations are realizing the benefits of processing data closer to its source, leading to reduced latency, security and compliance benefits, and more efficient bandwidth utilization as well as supporting scenarios where networking has challenging constraints.

Running Apache Kafka at the Edge Requires Confluent's Enterprise-Grade Data Streaming Platform

Modern edge computing is transforming industries including manufacturing, healthcare, transportation, defense, retail, energy, and much more—pushing data management to far-reaching data sources to enable connected, low latency operations and enhanced decision making. These new use cases shift workloads to the left—requiring real-time data streaming and processing at the edge, right where the data is generated.

Amazon OpenSearch Ingestion Adds Support for Confluent Cloud as Source

Until recently, customers didn't have an easy way to send data from Confluent’s data streaming platform to Amazon OpenSearch. They had to either write custom code using AWS Lambda as an intermediary, refactor the HTTP Sink connector, or self-manage an old Elasticsearch connector version. Earlier this year, we announced the fully managed OpenSearch Sink connector, providing a seamless way to sink data from Confluent to Amazon OpenSearch.