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11 个仓库

Awesome GitHub RepositoriesGeospatial Query Mapping

Translating structured spatial functions into native geographic query filters and distance calculations.

Distinct from Geospatial Mapping: Closest candidates are generic mapping tools or visualization libraries, not SQL-to-native query translation for geospatial filters.

Explore 11 awesome GitHub repositories matching data & databases · Geospatial Query Mapping. Refine with filters or upvote what's useful.

Awesome Geospatial Query Mapping GitHub Repositories

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  • nlpchina/elasticsearch-sqlNLPchina 的头像

    NLPchina/elasticsearch-sql

    7,012在 GitHub 上查看↗

    This project provides a SQL interface for Elasticsearch, serving as a translator and database layer that allows users to retrieve, filter, and manipulate indices using structured query language. It functions by converting standard SQL statements into the native JSON query language used by the search engine. The system includes a geospatial SQL engine for executing location-based searches and distance calculations. It also features a query debugger used to visualize the translation process from SQL to search engine request bodies to verify the logic and accuracy of data retrieval. The capabil

    Translates standard SQL spatial functions into specialized geographic query filters and distance calculations.

    Java
    在 GitHub 上查看↗7,012
  • redisearch/redisearchRediSearch 的头像

    RediSearch/RediSearch

    6,161在 GitHub 上查看↗

    RediSearch is a Redis module that adds secondary indexing, full-text search, aggregation, and vector similarity search directly into the in-memory data store. It operates as an in-process search engine, extending the core key-value store with capabilities for indexing hash and JSON documents, enabling fast field-level lookups beyond primary key access. The module provides a full-text search engine built on inverted indexes, supporting stemming, fuzzy matching, and relevance scoring via tf-idf. It also includes a vector similarity search engine using a Hierarchical Navigable Small World graph

    Restricts query results to documents within a numeric range or geographic area using indexed filters.

    Cfulltextgeospatialgis
    在 GitHub 上查看↗6,161
  • 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

    Creates geospatial indexes on columns to accelerate location-based queries.

    Java
    在 GitHub 上查看↗6,098
  • greptimeteam/greptimedbGreptimeTeam 的头像

    GreptimeTeam/greptimedb

    5,968在 GitHub 上查看↗

    GreptimeDB is a distributed, open-source time-series database built for unified observability. It stores and queries metrics, logs, and traces together in a single columnar engine, supporting both SQL and PromQL for analysis. The database is designed as a Kubernetes-native operator with a decoupled compute and storage architecture, enabling horizontal scaling and multi-region deployment. What distinguishes GreptimeDB is its role as a multi-protocol ingestion gateway, accepting data through OpenTelemetry, Prometheus Remote Write, InfluxDB, Loki, Elasticsearch, Kafka, and MQTT protocols without

    GreptimeDB uses Geohash, H3, or S2 indexing functions to perform spatial queries on location-tagged data.

    Rustanalyticscloud-nativedatabase
    在 GitHub 上查看↗5,968
  • tidwall/buntdbtidwall 的头像

    tidwall/buntdb

    4,834在 GitHub 上查看↗

    BuntDB is an embedded key-value store for Go applications, providing in-memory storage with optional disk persistence. It structures data using a B-tree for ordered key-value access and an R-tree for spatial indexing, allowing both range scans and geometric intersection queries. Support for indexing on nested JSON document fields enables efficient lookups by values within JSON objects, and per-key time-to-live (TTL) expiration automatically removes stale entries. The store uses copy-on-write transaction isolation, ensuring each transaction sees a consistent snapshot and changes are applied at

    Retrieve all items that intersect a given region from an R-tree spatial index.

    Godatabasegeospatialgolang
    在 GitHub 上查看↗4,834
  • 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。

    Filters records using polygon and bounding box queries to identify intersecting geometry.

    PLpgSQL
    在 GitHub 上查看↗4,730
  • shapely/shapelyshapely 的头像

    shapely/shapely

    4,455在 GitHub 上查看↗

    Shapely 是一个用于操作和分析平面几何对象的库,作为 GEOS C++ 引擎的 Python 封装器。它提供了一个框架,用于在笛卡尔平面内计算几何属性、评估空间关系和执行拓扑谓词。 该项目以其矢量化几何处理器脱颖而出,该处理器能够跨大型形状数组执行空间操作以提高吞吐量。它还包括一个基于 R-trees 的空间索引系统,以加速相交几何和最近邻的检索。 该库涵盖了广泛的功能,包括用于计算并集和交集的几何集合运算、在 GeoJSON 和 Well-Known Text 等格式之间的空间数据序列化,以及用于验证和修复几何拓扑的工具。它进一步支持几何变换、缓冲以及生成凸包或 Voronoi 图。

    Implements R-tree spatial indexing to accelerate the retrieval of intersecting geometries and nearest neighbors.

    Python
    在 GitHub 上查看↗4,455
  • apache/incubator-kvrocksapache 的头像

    apache/incubator-kvrocks

    4,339在 GitHub 上查看↗

    Kvrocks 是一个基于磁盘的 NoSQL 数据库和分布式键值存储,利用 RocksDB 存储引擎将大数据集持久化到物理磁盘。它被设计为 Redis 兼容数据库,利用标准的 Redis 通信协议确保与现有客户端库和工具的互操作性。 该项目的独特之处在于将磁盘持久化存储模型与高级检索能力相结合,包括用于 k-近邻查询的向量搜索、全文搜索索引和地理空间查询执行。它支持具有基于槽位(slot)的数据分布和拓扑管理的分布式集群,以实现水平扩展和高可用性。 该系统涵盖了广泛的数据存储类型,包括 JSON 文档、流、有序集合、哈希映射和位图。它提供了全面的数据管理工具,如原子事务、基于日志的复制以及用于基数估计和成员检查的概率数据结构。此外,它还包括服务端脚本、发布/订阅消息传递以及针对服务器健康状况和存储引擎性能的详细监控。

    Implements geospatial indexing to calculate distances and find members within a specific radius.

    C++
    在 GitHub 上查看↗4,339
  • apache/kvrocksapache 的头像

    apache/kvrocks

    4,338在 GitHub 上查看↗

    Kvrocks 是一个分布式键值存储和 Redis 兼容的 NoSQL 数据库。它利用 RocksDB 存储引擎提供基于磁盘的持久化,与内存系统相比,允许以更低的内存成本进行大容量数据存储。 该系统作为向量数据库和全文搜索引擎,支持对向量嵌入进行近邻搜索,并通过文本匹配进行复杂的文档查询。它采用无代理(proxyless)集群架构,通过基于槽位的路由来分发数据并在多个节点间扩展容量。 该平台涵盖了广泛的数据管理能力,包括 JSON 文档管理、时序数据和实时流处理。它通过地理空间查询、二级索引和查询计划分析提供高级搜索和索引功能,同时提供用于内存高效的基数和成员估计的概率数据草图。 其他操作特性包括原子事务、发布/订阅消息传递以及用于多租户环境的命名空间数据隔离。

    Implements geospatial indexing for location-based searches and distance calculations.

    C++databasedistributedkv
    在 GitHub 上查看↗4,338
  • nixzhu/dev-blognixzhu 的头像

    nixzhu/dev-blog

    3,906在 GitHub 上查看↗

    该项目是一个综合性的 iOS 应用开发框架,专注于构建具有自定义用户界面组件、异步任务管理和本地数据持久化的移动应用。它作为软件工程的技术知识库,提供用于以 Markdown 格式组织和发布架构分析与笔记的工具。 该框架通过一个强大的基于文档的存储层脱颖而出,该层利用 BSON 格式的记录在 NoSQL 文档存储中执行 CRUD 操作。它提供广泛的系统集成功能,包括专门的应用扩展通信、跨沙盒消息传递和原生共享表单呈现,从而允许宿主应用与系统级服务之间的无缝交互。 该项目涵盖了广泛的功能面,包括具有线程安全同步的高级并发管理、卸载到后台的 UI 渲染以保持响应性,以及全面的国际化支持。它还包括面向开发者的工具,用于静态类型生成、自动化资源映射和交互式原型构建,以及用于地理信标监控和自适应图表生成的专门工具。

    Filters data based on geographic coordinates to retrieve records within specific map bounding boxes.

    在 GitHub 上查看↗3,906
  • hdt3213/godisHDT3213 的头像

    HDT3213/godis

    3,836在 GitHub 上查看↗

    Godis is a Redis-compatible in-memory database and distributed key-value store. It functions as a replicated data store and distributed message broker, implementing the Redis protocol to manage complex data structures in memory. The system provides a geospatial indexing engine for proximity-based queries and distance calculations. It ensures high availability and data durability through master-slave replication and write-ahead logging. The project covers a wide range of capabilities including the management of strings, hash maps, lists, and sorted sets. It supports distributed data clusterin

    Provides geospatial indexing for efficient proximity-based queries and radius searches.

    Goclustergogodis
    在 GitHub 上查看↗3,836
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  3. Geospatial Query Mapping

探索子标签

  • Geospatial Indexes3 个子标签Using Geohash, H3, or S2 indexing functions to perform spatial queries on location-tagged data. **Distinct from Geospatial Query Mapping:** Distinct from Geospatial Query Mapping: focuses on the indexing functions themselves (Geohash, H3, S2) rather than the translation of spatial functions into query filters.
  • Polygon and Box FiltersSpecific query mechanisms for identifying points within defined polygonal or rectangular boundaries. **Distinct from Geospatial Query Mapping:** Specializes general geospatial mapping into concrete polygon and bounding box intersection queries
  • R-Tree Spatial IndexesMulti-dimensional tree indexes that store bounding boxes and enable geometric intersection queries for spatial data. **Distinct from Geospatial Query Mapping:** Distinct from Geospatial Query Mapping: focuses on the R-tree data structure for spatial indexing, not the translation of spatial functions into query filters.