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Awesome GitHub RepositoriesQuery Fan-out

Splitting a single global request into multiple parallel queries across distributed data sources.

Distinct from Distributed Query Processing: Focuses on the specific distribution of a query to multiple data sources, distinct from general distributed processing.

Explore 3 awesome GitHub repositories matching data & databases · Query Fan-out. Refine with filters or upvote what's useful.

Awesome Query Fan-out GitHub Repositories

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  • thanos-io/thanosthanos-io 的头像

    thanos-io/thanos

    14,121在 GitHub 上查看↗

    Thanos is a distributed metrics query engine and monitoring scalability suite designed to provide a unified interface for aggregating data from multiple Prometheus servers and clusters. It functions as a high availability monitoring backend that eliminates single points of failure by deduplicating data from replicated instances. The system enables long-term retention by persisting time-series data to cloud-native object storage, allowing for unlimited historical archiving beyond the limits of local disks. It further optimizes this storage through a downsampling and retention manager that comp

    Splits a single global request into multiple parallel queries across distributed data sources to aggregate a unified result.

    Gocncfgogoogle-cloud-storage
    在 GitHub 上查看↗14,121
  • apache/pinotapache 的头像

    apache/pinot

    6,098在 GitHub 上查看↗

    Pinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It functions as a real-time OLAP datastore, enabling interactive, user-facing analytics by ingesting and querying massive datasets from both streaming and batch sources. The system architecture relies on a centralized controller for cluster coordination and a distributed segment-based storage model to ensure horizontal scalability. The platform distinguishes itself through a hybrid ingestion pipeline that unifies real-time event streams and historical batch data into a single quer

    Processes simple analytic queries by fanning out requests to servers and merging partial results to minimize overhead.

    Java
    在 GitHub 上查看↗6,098
  • m3db/m3m3db 的头像

    m3db/m3

    4,895在 GitHub 上查看↗

    m3 是一个分布式时间序列数据库,专为高分辨率指标和高基数数据管理而设计。它作为一个可扩展的存储系统和多集群查询引擎,提供了一个分布式指标聚合器,能够在数据提交到存储之前进行降采样和汇总。 该项目以其使用 etcd 进行节点成员管理和分片放置的协调集群模型而脱颖而出。它支持多种摄取协议,包括 Prometheus 远程写入协议、InfluxDB 行协议和 Graphite Carbon 纯文本协议,并提供与 PromQL 和 Graphite 兼容的查询接口。 该系统涵盖了广泛的功能领域,包括列式时间序列存储、同步数据复制和分布式查询扇出。它集成了数据生命周期自动化、基于法定人数 (Quorum) 的一致性调整,以及基于标签的序列索引,以在隔离的命名空间中保持数据完整性和检索速度。 集群编排和组件放置通过自动化工具和 Operator 进行管理,以确保高可用性和均衡的数据分布。

    Splits global requests into parallel queries across distributed data sources and clusters.

    Go
    在 GitHub 上查看↗4,895
  1. Home
  2. Data & Databases
  3. Distributed Query Processing
  4. Query Fan-out

探索子标签

  • Time SeriesDistributed query mechanisms specifically for retrieving and stitching time-series data across clusters. **Distinct from Query Fan-out:** Focuses on the domain of time-series data stitching rather than general distributed request dispatching