RisingWave started as a distributed streaming database with a PostgreSQL interface. We wanted to make it easy to process real-time data using standard SQL. But we quickly realized that many teams don’t just want to process streaming data — they want to store it in a way that’s reusable by other tools downstream. - Source: dev.to / 10 days ago

This month (April 2025) marks 4 years and 1 month since I started building RisingWave. - Source: dev.to / 12 days ago

When we started RisingWave four years ago, we set out with a bold mission: to democratize stream processing (check our original blog here). Back then, building real-time streaming applications felt like climbing a mountain. It required specialized infrastructure, deep engineering know-how, and a hefty operational commitment. Stream processing had incredible potential, but its sheer complexity kept it locked away... - Source: dev.to / 15 days ago

RisingWave is a unified real-time data processing and management platform. It allows users to ingest, process, and query streaming data using familiar SQL. For this demonstration, we'll particularly leverage RisingWave's materialized views, which continuously and incrementally compute results as new data arrives, enabling real-time analysis without constant re-computation. Additionally, its Python SDK simplifies... - Source: dev.to / 15 days ago

Real-time pipelines might need RisingWave or Apache Kafka. - Source: dev.to / 22 days ago

Apache Flink, known initially as Stratosphere, is a distributed stream processing engine initiated by a group of researchers at TU Berlin. Since its initial release in May 2011, Flink has gained immense popularity in both academia and industry. And it is currently the most well-known streaming system globally (challenge me if you think I got it wrong!). - Source: dev.to / 5 days ago

Apache Iceberg defines a table format that separates how data is stored from how data is queried. Any engine that implements the Iceberg integration — Spark, Flink, Trino, DuckDB, Snowflake, RisingWave — can read and/or write Iceberg data directly. - Source: dev.to / 10 days ago

The last decade saw the rise of open-source frameworks like Apache Flink, Spark Streaming, and Apache Samza. These offered more flexibility but still demanded significant engineering muscle to run effectively at scale. Companies using them often needed specialized stream processing engineers just to manage internal state, tune performance, and handle the day-to-day operational challenges. The barrier to entry... - Source: dev.to / 15 days ago

Apache Flink: Flink is a unified streaming and batching platform developed under the Apache Foundation. It provides support for Java API and a SQL interface. Flink boasts a large ecosystem and can seamlessly integrate with various services, including Kafka, Pulsar, HDFS, Iceberg, Hudi, and other systems. - Source: dev.to / 23 days ago

In conclusion, Apache Flink is more than a big data processing tool—it is a thriving ecosystem that exemplifies the power of open source collaboration. From its impressive technical capabilities to its innovative funding model, Apache Flink shows that sustainable software development is possible when community, corporate support, and transparency converge. As industries continue to demand efficient real-time data... - Source: dev.to / about 2 months ago