For bază de date pentru hărți și interogări geo, the strongest matches are tidwall/tile38 (Tile38 is a dedicated geospatial database with spatial indexing), sqlite/sqlite (SQLite is a serverless embedded database engine that includes) and mongodb/mongo (MongoDB is a document database that includes built-in support). Each is ranked by relevance to your query, popularity and recent activity.
Motoare de baze de date și extensii open-source concepute pentru stocarea, indexarea și interogarea datelor geografice complexe.
Tile38 is an in-memory geospatial database that uses the Redis protocol for communication and query execution. It serves as a distributed spatial store for points and polygons, featuring high availability through leader-follower replication and disk-based persistence. The system includes a real-time geofencing engine that monitors virtual geographic boundaries and triggers webhooks when objects enter or exit specified areas. It further distinguishes itself with an embedded Lua scripting engine for server-side data transformations and a built-in vector tile server for efficient map visualizati
Tile38 is a dedicated geospatial database with spatial indexing, real-time geofencing, and support for points and polygons, making it a strong fit for a spatial database system despite being in-memory and Redis-protocol-based.
SQLite is a serverless relational database engine and C-based library that stores data in a single local disk file. It functions as an embedded SQL database, integrating directly into applications without the need for a separate server process. The engine includes specialized capabilities for full-text search indexing and spatial data querying using R-Tree structures for geographic or geometric coordinate ranges. The system provides broad support for SQL data manipulation, database recovery and repair, and change tracking for synchronizing modifications between databases. It also features a
SQLite is a serverless embedded database engine that includes dedicated R-Tree indexing for spatial querying of geometric coordinates, making it a genuine option for storing and querying spatial data even though it lacks advanced geospatial features like CRS handling or standard format support.
This project is a distributed, document-oriented database system designed to store information in flexible, hierarchical structures. It supports horizontal scaling through automated sharding and maintains high availability across global clusters using a multi-node replication protocol. By executing multi-document operations as atomic units, the system ensures data integrity and consistency across distributed environments. The platform distinguishes itself by integrating advanced vector-based indexing, which enables semantic similarity searches alongside traditional geospatial and lexical quer
MongoDB is a document database that includes built-in support for GeoJSON data types, 2dsphere and 2d spatial indexes, and geospatial query operators ($near, $geoWithin, etc.), making it a genuine though general-purpose option for storing and querying geographic data.