Confluent has announced advancements in Tableflow, facilitating easier access to operational data from data lakes and warehouses.
Tableflow allows all streaming data within Confluent Cloud to be accessed in popular open table formats. This capability enables enhanced analytics, real-time artificial intelligence (AI), and next-generation applications. The company has made support for Apache Iceberg generally available and has expanded its partnership with Databricks to introduce a new early access programme for Delta Lake. Additionally, Tableflow now provides increased data storage flexibility and smoother integrations with catalog providers such as AWS Glue Data Catalog and Snowflake's managed service.
"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 challenges faced by many AI projects, often due to disconnected data, were highlighted in the IDC FutureScape: Worldwide Digital Infrastructure 2025 Predictions. The report notes, "By 2027, after suffering multiple AI project failures, 70% of IT teams will return to basics and focus on AI-ready data infrastructure platforms." It further elaborates, "Many IT organisations 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."
Contemporary consumer expectations require applications to understand current business status and customer interactions autonomously. For instance, AI in inventory management should be capable of recognising trends, alerting manufacturers of demand spikes, and providing delivery estimates. Real-time data flow is essential to this efficiency, which conventional batch processing methods cannot achieve.
Brady Perry, Co-founder at Busie, commented on the utility of Tableflow by saying, "Transportation companies love us because we make sales, operations, and dispatching super simple, but that's only possible with real-time data analytics. 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."
Tableflow aims to streamline the connection between operational and analytical systems. It maintains a continuous update of analytics and AI tables using data directly from business applications linked to Confluent Cloud. Such functionality ensures that generated data is processed and governed immediately, providing consistent, high-quality data for data lakes and warehouses.
The newly announced updates to Tableflow include production-grade support for Apache Iceberg, allowing teams to represent Apache Kafka topics as Iceberg tables for both real-time and batch processing purposes. It also introduces a new Early Access Programme for Delta Lake, facilitating a uniform real-time data view for enhanced AI-driven decision-making processes.
The updates further extend the flexibility of Bring Your Own Storage, where customers can opt for storage solutions that fit their compliance and data ownership needs. Integrations with partners such as Amazon SageMaker Lakehouse and Snowflake Open Catalog are designed to enhance data accessibility and streamline catalog management.
Confluent also boosts enterprise adoption of Tableflow by collaborating with system integrators including GoodLabs Studio, Onibex, Psyncopate, and Tata Consultancy Services.
