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5 个仓库

Awesome GitHub RepositoriesJSON Query Executions

Executing search queries defined in JSON format with support for dynamic parameter injection.

Distinct from JSON Query Constraints: Closest candidates focus on graph constraints or general APIs; this is specifically about running JSON-based search queries against a data store.

Explore 5 awesome GitHub repositories matching data & databases · JSON Query Executions. Refine with filters or upvote what's useful.

Awesome JSON Query Executions GitHub Repositories

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  • 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

    Supports extraction, validation, and transformation of nested JSON objects using path expressions.

    Java
    在 GitHub 上查看↗6,098
  • zombodb/zombodbzombodb 的头像

    zombodb/zombodb

    4,730在 GitHub 上查看↗

    Zombodb 是一个将 PostgreSQL 与 Elasticsearch 集成的数据库扩展和关系数据索引器。它提供了一个 SQL 搜索接口,允许用户使用标准 SQL 函数和语法(而非原生 JSON API)执行复杂的搜索查询和聚合。该项目将关系数据从 PostgreSQL 同步到远程搜索引擎,以实现高性能的全文本搜索和分析。 该系统通过将关系结构与搜索引擎能力桥接而脱颖而出,特别是通过针对几何和地理类型的地理空间搜索集成。它实现了一个 SQL 转 JSON 的查询映射层,支持在关系环境中直接进行高级文本分析,包括模糊匹配、邻近搜索和相关性评分。 该项目涵盖了广泛的能力领域,包括索引生命周期管理、自动化关系数据同步和复杂的分析聚合。它支持用于基于位置查询的空间索引、自定义文本分析管道,以及用于审计索引统计和集群健康的监控工具。安全性通过使用 TLS 在数据库和搜索引擎之间进行加密连接来处理。

    Allows executing search queries defined in raw JSON format to access advanced search engine features.

    PLpgSQL
    在 GitHub 上查看↗4,730
  • datlechin/tableprodatlechin 的头像

    datlechin/TablePro

    4,471在 GitHub 上查看↗

    TablePro is a cross-platform database management client designed for browsing, querying, and administering both SQL and NoSQL databases. It functions as a unified workspace that integrates a code-centric SQL editor with schema visualization tools, allowing developers to manage complex data models and execute queries across diverse database engines. The application distinguishes itself through an agentic AI integration layer that connects language models directly to database tools, enabling automated query generation, optimization, and error fixing with configurable approval gates. It features

    Provides a console for executing search requests and rendering responses as grids or formatted JSON.

    Swift
    在 GitHub 上查看↗4,471
  • itchyny/gojqitchyny 的头像

    itchyny/gojq

    3,770在 GitHub 上查看↗

    gojq is a JSON query engine and transformation tool implemented in Go. It serves as a Go language port of the jq command, providing a library for embedding JSON and YAML manipulation capabilities directly into Go applications. The tool functions as an arbitrary-precision JSON processor, performing mathematical operations on large integers to prevent precision loss or numeric overflow during data transformations. Its broader capabilities include filtering and reshaping structured data using a specialized query language, converting between YAML and JSON formats, and formatting date and time st

    Parses and runs filter strings against JSON-compatible data to extract or modify specific information.

    Go
    在 GitHub 上查看↗3,770
  • spring-projects/spring-data-elasticsearchspring-projects 的头像

    spring-projects/spring-data-elasticsearch

    2,959在 GitHub 上查看↗

    Spring Data Elasticsearch is a data access library that maps Java objects to Elasticsearch indices. It functions as an object mapper, a repository abstraction, and a query DSL wrapper, providing both a standard and a reactive client for executing asynchronous search and persistence operations. The project distinguishes itself by automating data access through repository interfaces, which generate query logic based on method naming conventions. It enables the construction of complex search queries using a domain-specific language and supports advanced search capabilities such as vector similar

    Enables the execution of specific JSON queries using positional placeholders or expressions for dynamic parameterization.

    Java
    在 GitHub 上查看↗2,959
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