2 个仓库
Groups continuous event streams into specific time intervals to calculate periodic metrics.
Distinct from Event Stream Aggregators: Focuses on periodic metric calculation via windowing rather than just presenting a chronological API stream.
Explore 2 awesome GitHub repositories matching data & databases · Windowed Event Aggregations. Refine with filters or upvote what's useful.
This project is a collection of educational resources and reference implementations for the Apache Flink stream processing framework. It provides a learning resource focused on mastering distributed stream processing through implementation guides, performance tuning tutorials, and practical examples. The repository features detailed walkthroughs for building real-time data pipelines using the DataStream and Table APIs. It includes specific integration examples for connecting Apache Flink with Kafka brokers and Elasticsearch indices, as well as reference implementations for real-time deduplica
Groups continuous data flows into temporal or count-based windows to perform periodic aggregations.
RisingWave is a cloud-native streaming database and real-time analytics engine that uses standard SQL to process continuous data streams. It functions as a streaming data lakehouse, combining the capabilities of a streaming SQL database with a platform that integrates streaming ingestion with open table formats. The system is distinguished by its use of the PostgreSQL wire protocol, allowing it to integrate with existing SQL tools and drivers. It employs a decoupled compute and storage architecture, persisting streaming state and materialized views in cloud object storage to enable independen
Groups continuous event flows into time intervals to calculate periodic metrics.