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Confluent Announces the General Availability of Tableflow

March 19, 2025 --

Confluent, Inc. (NASDAQ:CFLT), the data streaming pioneer, today announced significant advancements in Tableflow, the easiest way to access operational data from data lakes and warehouses. With Tableflow, all streaming data in Confluent Cloud can be accessed in popular open table formats, unlocking limitless possibilities for advanced analytics, real-time artificial intelligence (AI), and next-generation applications. Support for Apache Iceberg™ is now generally available (GA). And as a result of an expanded partnership with Databricks, a new early access program for Delta Lake is now open. Additionally, Tableflow now offers enhanced data storage flexibility and seamless integrations with leading catalog providers, including AWS Glue Data Catalog and Snowflake’s managed service for Apache Polaris™, Snowflake Open Catalog.

“At Confluent, we’re all about making your data work for you, whenever you need it and in whatever format is required,” said Shaun Clowes, Chief Product Officer at Confluent. “With Tableflow, we’re bringing our expertise of connecting operational data to the analytical world. Now, data scientists and data engineers have access to a single, real-time source of truth across the enterprise, making it possible to build and scale the next generation of AI-driven applications.”

The Downfall of AI Projects: Disconnected Data

“By 2027, after suffering multiple AI project failures, 70% of IT teams will return to basics and focus on AI-ready data infrastructure platforms,” claimed IDC in the IDC FutureScape: Worldwide Digital Infrastructure 2025 Predictions. The report added, “Many IT organizations rely on scores of data silos and a dozen or more different copies of data. These silos and redundant data stores can be a major impediment to effective AI model development.”

AI projects are failing because old development methods cannot keep pace with new consumer expectations. These applications are expected to know the current status of a business and its customers and take action automatically. For example, an AI agent for inventory management should be able to identify if a particular item is trending, immediately notify manufacturers of the increased demand, and provide an accurate delivery estimate for customers. This level of hands-free efficiency is simply not possible if business data is not getting to the analytics and AI systems in real time. The old ways of batch processing lead to inaccurate results, and manually copying over data is unstable, not scalable, and proliferates the silo problem.

Bridging the Data Gap for Enterprise-Ready AI

“Transportation companies love us because we make sales, operations, and dispatching super simple, but that’s only possible with real-time data analytics,” said Brady Perry, Co-founder at Busie. “Tableflow offers a promising path for our analytics engine to seamlessly consume operational data in Kafka in real time as Apache Iceberg tables, eliminating the need for additional preprocessing. By integrating Tableflow with Snowflake, we could prevent raw, unclean data from being ingested while reducing complexity and storage costs. This approach would simplify workflows and accelerate time to insight while ensuring a more efficient and cost-effective data architecture.”

Tableflow simplifies the integration between operational data and analytical systems. It continuously updates tables used for analytics and AI with the exact same data from business applications connected to Confluent Cloud. Within Confluent, processing and governance happen as data is generated, shifting these tasks upstream to ensure that only high-quality, consistent data is used to feed data lakes and warehouses. This is a breakthrough for AI, as it’s only as powerful as the data that shapes it.

Today, Confluent announces significant updates to Tableflow:

  • Support for Apache IcebergTM is ready for production workloads. Teams can now instantly represent Apache Kafka® topics as Iceberg tables to feed any data warehouse, data lake, or analytics engine for real-time or batch processing use cases. Expensive and error-prone table maintenance tasks, such as compaction, are automatically handled by Tableflow, giving time back to data engineers to deliver more business value. It also provides a single source of truth for one of the most widely adopted open-format storage options, enabling data scientists and data engineers to scale AI innovation and next-generation applications.
  • New Early Access Program for Delta Lake is now open. This open-format storage layer, pioneered by Databricks, processes more than 10 exabytes of data daily and is used alongside many popular AI engines and tools. With this integration, customers will have a consistent view of real-time data across operational and analytic applications, enabling faster, smarter AI-driven decision-making. Apply for the Tableflow Early Access Program here.
  • Increase flexibility through Bring Your Own Storage. Store fresh, up-to-date Iceberg or Delta tables once and reuse them many times with the freedom to choose a storage bucket. Customers now have full control over storage and compliance to meet their unique data ownership needs.
  • Enhance data accessibility and governance with partners. Direct integrations with Amazon SageMaker Lakehouse via AWS Glue Data Catalog (GA) and Snowflake Open Catalog (GA) enable seamless catalog management for Tableflow’s Iceberg tables. They also streamline access for analytical engines such as Amazon Athena, Amazon EMR, and Amazon RedShift, and leading data lake and warehouse solutions including Snowflake, Dremio, Imply, Onehouse, and Starburst. Additionally, Confluent has strengthened enterprise adoption for Tableflow with support from global and regional system integrators, including GoodLabs Studio, Onibex, Psyncopate, and Tata Consultancy Services (TCS).

These announcements will be spotlighted on the main stage of Current Bengaluru on March 19 at 10:00 a.m. Indian Standard Time. Register here to attend virtually.

Additional Resources

About Confluent

Confluent is the data streaming platform that is pioneering a fundamentally new category of data infrastructure that sets data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion—designed to be the intelligent connective tissue enabling real-time data from multiple sources to constantly stream across an organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven back-end operations. To learn more, please visit www.confluent.io.

As our road map may change in the future, the features referred to here may change, may not be delivered on time, or may not be delivered at all. This information is not a commitment to deliver any functionality, and customers should make their purchasing decisions based on features that are currently available.

Confluent® and associated marks are trademarks or registered trademarks of Confluent, Inc.

Apache®, Apache Kafka®, Kafka®, Apache Flink®, Flink®, Apache Iceberg™, Iceberg™, Apache Polaris™, and Polaris™ are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries. No endorsement by the Apache Software Foundation is implied by the use of these marks. All other trademarks are the property of their respective owners.

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