Confluent Unveils Tableflow and Enhances Apache Flink for Advanced AI and Analytics Capabilities

Confluent expands AI and analytics capabilities in Apache Flink and Tableflow - SiliconANGLE

Confluent expands AI and analytics capabilities in Apache Flink and Tableflow Streaming data software provider Confluent Inc. today announced new artificial intelligence and analytics capabilities designed to simplify real-time data processing and enterprise intelligence. The announcements include updates to Confluent Cloud for Apache Flink that introduce what it says is seamless AI model inference, vector search and built-in machine learning functions. Meanwhile, enhancements to Tableflow improve access to operational data in real-time analytics environments, with expanded support for Apache Iceberg and Delta Lake. The new updates in Confluent Cloud for Apache Flink are designed to streamline and simplify the process of developing real-time AI applications. The service now supports Flink Native Inference, which cuts through complex workflows by allowing teams to run any open-source AI model directly in Confluent Cloud. A new Flink search feature unifies data access across multiple vector databases to streamline discovery and retrieval within a single interface and new built-in machine learning functions bring AI-driven use cases, such as forecasting and anomaly detection, directly into Flink SQL. Confluent is pitching the innovations as redefining how businesses can harness AI for real-time customer engagement and decision-making. "Building real-time AI applications has been too complex for too long, requiring a maze of tools and deep expertise just to get started," explains Shaun Clowes, chief product officer at Confluent. "With the latest advancements in Confluent Cloud for Apache Flink, we're breaking down those barriers -- bringing AI-powered streaming intelligence within reach of any team." Alongside the Confluent Cloud for Apache Flink's new features, Confluent also announced advances in Tableflow, the company's data integration solution that enables real-time access to operational data in open table formats for advanced analytics and AI applications. The latest update makes Apache Iceberg support generally available, allowing teams to instantly transform Apache Kafka topics into Iceberg tables for integration with data warehouses and analytics engines. The service eliminates the need for complex preprocessing, reducing operational overhead and ensuring a consistent, real-time source of truth for AI-driven applications. Confluent also launched an early access program for Delta Lake, expanding Tableflow's compatibility with Databricks' open-format storage layer. The integration enables faster decision-making and more efficient AI workflows by maintaining a unified view of real-time data across operational and analytical applications, Additional enhancements include bring your own storage options and deeper integrations with catalog providers like AWS Glue and Snowflake Open Catalog, which give enterprises greater flexibility and governance control over their data. "With Tableflow, we're bringing our expertise of connecting operational data to the analytical world," said Clowes. "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."

Confluent Unveils General Availability of Tableflow to Power GenAI Apps

The company has also expanded its partnership with Databricks, introducing an early access program for Delta Lake. Data streaming company Confluent has announced the general availability (GA) of Tableflow, a solution designed to bridge operational and analytical data for real-time AI and next-generation applications. The announcement was made at Confluent's data streaming event Current 2025 in Bengaluru. With Tableflow, data streaming in Confluent Cloud is now accessible in popular open table formats, unlocking advanced analytics and AI-driven decision-making. A key highlight of the launch is the full production readiness of Apache Iceberg support, allowing Apache Kafka topics to be represented as Iceberg tables. "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 in 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." Moreover, Confluent has expanded its partnership with Databricks, introducing an early access program for Delta Lake, providing customers with a consistent real-time data view across operational and analytical applications. The latest update to Tableflow introduces several enhancements to improve AI-driven data access and management. With general availability for Apache Iceberg support, teams can now seamlessly convert Kafka topics into Iceberg tables, eliminating manual data transfers and enhancing AI scalability. The new Delta's Lake early access program, developed in collaboration with Databricks, allows customers to use Delta Lake's open-format storage layer, which processes over 10 exabytes of data daily, for real-time analytics. Furthermore, Tableflow now supports a Bring Your Own Storage (BYOS) model, giving users full control over data storage and compliance by allowing them to store Iceberg or Delta tables in their preferred storage buckets. To further streamline analytical workflows, Tableflow offers enhanced data governance through direct integrations with Amazon SageMaker Lakehouse via AWS Glue Data Catalog and Snowflake Open Catalog. Tableflow has already drawn interest from enterprises using AI-driven analytics. Brady Perry, co-founder at Busie, noted, "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." Confluent has a number of partners across verticals, with prominent Indian players being Swiggy and Jio.

Confluent expands AI and analytics capabilities in Apache Flink and Tableflow

Confluent expands AI and analytics capabilities in Apache Flink and Tableflow Streaming data software provider Confluent Inc. today announced new artificial intelligence and analytics capabilities designed to simplify real-time data processing and enterprise intelligence. The announcements include updates to Confluent Cloud for Apache Flink that introduce what it says is seamless AI model inference, vector search and built-in machine learning functions. Meanwhile, enhancements to Tableflow improve access to operational data in real-time analytics environments, with expanded support for Apache Iceberg and Delta Lake. The new updates in Confluent Cloud for Apache Flink are designed to streamline and simplify the process of developing real-time AI applications. The service now supports Flink Native Inference, which cuts through complex workflows by allowing teams to run any open-source AI model directly in Confluent Cloud. A new Flink search feature unifies data access across multiple vector databases to streamline discovery and retrieval within a single interface and new built-in machine learning functions bring AI-driven use cases, such as forecasting and anomaly detection, directly into Flink SQL. Confluent is pitching the innovations as redefining how businesses can harness AI for real-time customer engagement and decision-making. "Building real-time AI applications has been too complex for too long, requiring a maze of tools and deep expertise just to get started," explains Shaun Clowes, chief product officer at Confluent. "With the latest advancements in Confluent Cloud for Apache Flink, we're breaking down those barriers -- bringing AI-powered streaming intelligence within reach of any team." Tableflow Alongside the Confluent Cloud for Apache Flink's new features, Confluent also announced advances in Tableflow, the company's data integration solution that enables real-time access to operational data in open table formats for advanced analytics and AI applications. The latest update makes Apache Iceberg support generally available, allowing teams to instantly transform Apache Kafka topics into Iceberg tables for integration with data warehouses and analytics engines. The service eliminates the need for complex preprocessing, reducing operational overhead and ensuring a consistent, real-time source of truth for AI-driven applications. Confluent also launched an early access program for Delta Lake, expanding Tableflow's compatibility with Databricks' open-format storage layer. The integration enables faster decision-making and more efficient AI workflows by maintaining a unified view of real-time data across operational and analytical applications, Additional enhancements include bring your own storage options and deeper integrations with catalog providers like AWS Glue and Snowflake Open Catalog, which give enterprises greater flexibility and governance control over their data. "With Tableflow, we're bringing our expertise of connecting operational data to the analytical world," said Clowes. "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."

Confluent Announces the General Availability of Tableflow

Tableflow brings real-time business context to analytical systems to make AI and next-generation applications enterprise-ready 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 Iceberg 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, AWS 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). Additional Resources Read the Tableflow GA product blog for a full rundown of what's new. Start your free trial of Confluent Cloud. No credit card required. Ask our Professional Services experts for faster adoption. 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 Announces the General Availability of Tableflow By Investing.com

Tableflow brings real-time business context to analytical systems to make AI and next-generation applications enterprise-ready BENGALURU, India--(BUSINESS WIRE)--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: 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. View source version on businesswire.com: https://www.businesswire.com/news/home/20250318342911/en/