The infrastructure behind AI agents isn't static—it’s a living, evolving system. Designing effective data pipelines means ...

To realize business value from generative AI, start small, iterate fast and scale smart—while ensuring strong data, team ...

We speak to Cern principal scientist Archana Sharma about pattern recognition, machine learning and quantum technology.

Apache Pinot’s major distinguishing features over other columnar analytic databases are its plug-in indexes, star-tree index, and ability to combine batch data with real-time data.

In the world of data processing and distributed systems, messaging queues and streaming platforms represent two fundamental approaches to handling real-time data. While they may appear similar at ...

Stream processing continuously processes data in real-time, making it ideal for real-time analytics, monitoring, and decision-making tasks (Edge Delta). Using stream processing, you can handle tasks ...

In reality, the opposite is true. Batch processing requires such regular and intensive spikes in processing power that it’s significantly less efficient than a continuous low-level stream.

Support for Java, Python, and SQL, with unified support for both batch and stream processing. Flink is a mature open-source project from the Apache Software Foundation and has a very active and ...