{"id":827320,"date":"2025-03-19T00:33:18","date_gmt":"2025-03-19T04:33:18","guid":{"rendered":"https:\/\/www.marketnewsdesk.com\/index.php\/confluent-announces-the-general-availability-of-tableflow\/"},"modified":"2025-03-19T00:33:18","modified_gmt":"2025-03-19T04:33:18","slug":"confluent-announces-the-general-availability-of-tableflow","status":"publish","type":"post","link":"https:\/\/www.marketnewsdesk.com\/index.php\/confluent-announces-the-general-availability-of-tableflow\/","title":{"rendered":"Confluent Announces the General Availability of Tableflow"},"content":{"rendered":"

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Confluent Announces the General Availability of Tableflow<\/b><\/p>\n

Tableflow brings real-time business context to analytical systems to make AI and next-generation applications enterprise-ready<\/i><\/p>\n

BENGALURU, India–(BUSINESS WIRE<\/a>)–Confluent, Inc<\/a>. (NASDAQ:CFLT), the data streaming pioneer, today announced significant advancements in Tableflow<\/a>, 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\u2122 is now generally available (GA). And as a result of an expanded partnership with Databricks<\/a>, 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\u2019s managed service for Apache Polaris\u2122, Snowflake Open Catalog<\/a>.\n<\/p>\n

\n\u201cAt Confluent, we\u2019re all about making your data work for you, whenever you need it and in whatever format is required,\u201d said Shaun Clowes, Chief Product Officer at Confluent. \u201cWith Tableflow, we\u2019re 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.\u201d\n<\/p>\n

The Downfall of AI Projects: Disconnected Data<\/b><\/p>\n

\n\u201cBy 2027, after suffering multiple AI project failures, 70% of IT teams will return to basics and focus on AI-ready data infrastructure platforms,\u201d claimed IDC in the IDC FutureScape: Worldwide Digital Infrastructure 2025 Predictions<\/a>. The report added, \u201cMany 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.\u201d\n<\/p>\n

\nAI 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.\n<\/p>\n

Bridging the Data Gap for Enterprise-Ready AI<\/b><\/p>\n

\n\u201cTransportation companies love us because we make sales, operations, and dispatching super simple, but that\u2019s only possible with real-time data analytics,\u201d said Brady Perry, Co-founder at Busie. \u201cTableflow 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.\u201d\n<\/p>\n

\nTableflow 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\u2019s only as powerful as the data that shapes it.\n<\/p>\n

\nToday, Confluent announces significant updates to Tableflow:\n<\/p>\n