Showing 4 open source projects for "high performance computing"

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  • 1
    Apache SeaTunnel

    Apache SeaTunnel

    SeaTunnel is a distributed, high-performance data integration platform

    SeaTunnel is a very easy-to-use ultra-high-performance distributed data integration platform that supports real-time synchronization of massive data. It can synchronize tens of billions of data stably and efficiently every day, and has been used in the production of nearly 100 companies. There are hundreds of commonly-used data sources of which versions are incompatible. With the emergence of new technologies, more data sources are appearing.
    Downloads: 3 This Week
    Last Update:
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  • 2
    StarRocks

    StarRocks

    StarRocks is a next-gen sub-second MPP database for full analytics

    ...Processing any updates or deletes once data arrives has not been possible- until now. StarRocks solves these challenges and makes real-time analytics easy. Get amazing query performance on Star or Snowflake Schemas directly. From canceled orders to updated items, your analytics applications can easily handle them with StarRocks. From streaming data to change data capture, StarRocks meets the data ingestion demands of real-time analytics. Scale storage and computing power horizontally and support tens of thousands of concurrent users. ...
    Downloads: 0 This Week
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  • 3
    BitSail

    BitSail

    BitSail is a distributed high-performance data integration engine

    BitSail is ByteDance's open source data integration engine which is based on distributed architecture and provides high performance. It supports data synchronization between multiple heterogeneous data sources, and provides global data integration solutions in batch, streaming, and incremental scenarios. At present, it serves almost all business lines in ByteDance, such as Douyin, Toutiao, etc., and synchronizes hundreds of trillions of data every day.
    Downloads: 0 This Week
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  • 4
    Apache Kafka

    Apache Kafka

    Mirror of Apache Kafka

    Apache Kafka is a distributed streaming platform built around durable, partitioned logs called topics, enabling high-throughput, fault-tolerant event pipelines. Producers append records to partitions, brokers replicate them for durability, and consumer groups read them at their own pace while balancing work across instances. The commit/offset model and retention policies support patterns from real-time processing to event sourcing and audit trails. Exactly-once processing semantics,...
    Downloads: 2 This Week
    Last Update:
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