Best Real-Time Data Streaming Tools for Redpanda Agentic Data Plane

Apache Kafka® is an open-source, distributed streaming platform. Scale production clusters up to a thousand brokers, trillions of messages per day, petabytes of data, hundreds of thousands of partitions. Elastically expand and contract storage and processing. Stretch clusters efficiently over availability zones or connect separate clusters across geographic regions. Process streams of events with joins, aggregations, filters, transformations, and more, using event-time and exactly-once processing. Kafka’s out-of-the-box Connect interface integrates with hundreds of event sources and event sinks including Postgres, JMS, Elasticsearch, AWS S3, and more. Read, write, and process streams of events in a vast array of programming languages.

Redpanda is pioneering the Agentic Data Plane (ADP) - a new category in AI infrastructure that makes it simple and secure to connect AI agents with enterprise data and systems. Built on a multi-modal data streaming engine, Redpanda empowers agentic applications that reason and act in real-time with speed, autonomy, and precision. Global leaders including Activision Blizzard, Cisco, Moody's, Texas Instruments, Vodafone and 2 of the top 5 banks in the U.S. rely on Redpanda to process hundreds of terabytes of data a day. Backed by premier venture investors Lightspeed, GV and Haystack VC, Redpanda is a diverse, people-first organization with teams distributed around the globe.

The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.

Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams. Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale. Any kind of data is produced as a stream of events. Credit card transactions, sensor measurements, machine logs, or user interactions on a website or mobile application, all of these data are generated as a stream. Apache Flink excels at processing unbounded and bounded data sets. Precise control of time and state enable Flink’s runtime to run any kind of application on unbounded streams. Bounded streams are internally processed by algorithms and data structures that are specifically designed for fixed sized data sets, yielding excellent performance. Flink is designed to work well each of the previously listed resource managers.