Mirror of Apache Samza
الميزات الرئيسية لـ apache/samza هي: Stream Processing, Streaming Engines.
تشمل البدائل مفتوحة المصدر لـ apache/samza: cocoindex-io/cocoindex — Cocoindex is an incremental data processing engine that builds and maintains live indexes for AI agents, with a core… emqx/kuiper — Lightweight data stream processing engine for IoT edge. apache/spark — Apache Spark is a unified distributed data processing engine designed for large-scale data analysis and computation… bytewax/bytewax — Python Stream Processing. apache/flink — Apache Flink is a distributed processing engine designed for both high-throughput, low-latency data streams and finite… hstreamdb/hstream — HStreamDB is an open-source, cloud-native streaming database for IoT and beyond. Modernize your data stack for…
Apache Spark is a unified distributed data processing engine designed for large-scale data analysis and computation graphs. It functions as a distributed machine learning framework, a graph processing system, a real-time stream processor, and a SQL analytics engine. The system enables the execution of distributed SQL querying, large-scale graph analysis, and real-time stream analytics across clusters of machines. It also provides a scalable environment for implementing machine learning algorithms and predictive model development on massive datasets. The engine incorporates relational query e
Apache Flink is a distributed processing engine designed for both high-throughput, low-latency data streams and finite batch workloads. It functions as a stateful stream processor and a SQL stream processing engine, providing a unified runtime to execute relational queries and event-based transformations. The system is distinguished by its ability to manage persistent operator state to ensure exactly-once processing guarantees and consistency during failures. It features specialized capabilities for complex event processing to detect temporal patterns and handles out-of-order events using eve
Cocoindex is an incremental data processing engine that builds and maintains live indexes for AI agents, with a core focus on codebase indexing and knowledge graph extraction. The engine uses a function-graph execution model where user-defined Python functions are composed into a directed acyclic graph, and it processes data incrementally so only changed source records or code paths are re-computed, avoiding full recomputation at any scale. It supports automatic schema inference from transformation pipeline type annotations and provides full data lineage tracing, tagging every output record wi
