Multi-Model Databases

SurrealDB is a multi-model database engine designed to store and query document, graph, relational, and vector data within a single ACID-compliant platform. It functions as an AI-native data store, integrating vector search, graph traversal, and machine learning model execution directly into its query layer. By providing a unified declarative query language, the platform eliminates the need for external middleware to synchronize data across different storage models. The platform distinguishes itself through its ability to manage agent memory and complex workflows natively. It allows developer

This project is a multi-model database system designed to store and manage information as documents, graphs, and key-value pairs within a single engine. It functions as a graph database and knowledge graph platform, providing the infrastructure to build, query, and visualize structured data models. By integrating vector search capabilities, the system serves as a vector database that supports retrieval-augmented generation for artificial intelligence applications. The platform distinguishes itself through a unified query language that allows users to perform document lookups, graph traversals

RoseDB is a persistent key-value database and log-structured storage engine. It functions as a lightweight storage system that utilizes a log-structured hash table and a Bitcask engine implementation to provide fast data retrieval and disk-backed persistence. The system operates as an atomic transaction engine, grouping multiple read and write operations into single units to maintain data consistency. It handles data through a key-value model that supports individual insertions, lookups, and deletions. The database provides capabilities for batch data processing and atomic updates. Additiona

This project is a MongoDB Eloquent ORM and NoSQL query builder for the Laravel framework. It provides an active record implementation that maps MongoDB collections and documents to programmable models for data manipulation. The system enables schemaless data management, allowing applications to handle dynamic data structures without the need for rigid database migrations or predefined tables. It integrates MongoDB into Laravel applications to store and retrieve flexible document data using standard PHP patterns. The library covers document store querying and Eloquent model mapping, utilizing

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

React Native AsyncStorage is a persistent key-value storage library designed for React Native applications. It provides a unified local storage interface that works identically on both iOS and Android, ensuring saved data remains available across app restarts and when the device has no network connectivity. The library uses an asynchronous background I/O queue to handle all storage operations without blocking the JavaScript thread, communicating with native storage engines through React Native's bridge protocol. It includes a serialization layer that converts JavaScript values to strings for

Bolt is a single-file embedded key-value store for Go applications. It is an ACID transactional database that organizes data in B+trees on disk to provide efficient sorted key retrieval and range scans. The system uses a memory-mapped model to map the database file directly into the process address space for fast random-access reads. The project distinguishes itself through a multi-version concurrency control architecture that allows multiple simultaneous readers to access a consistent snapshot of data without blocking a writer. It employs a single-writer multi-reader locking model and uses a

TinyDB is a lightweight, document-oriented database and embedded NoSQL engine. It stores data as documents in local files, providing a persistence layer that operates without a separate server process. The system is an extensible document store featuring a middleware architecture. This allows for the customization of storage backends and the interception of data operations to transform how information is stored and retrieved. The database manages unstructured data using JSON-based serialization and supports pluggable storage backends for local file persistence.

MapDB is an embedded database engine and disk-backed collection library that stores Java collections on disk or off-heap. It functions as a local data processing engine designed to handle datasets that exceed available physical RAM. The project utilizes off-heap data storage to eliminate garbage collection overhead and employs disk overflow caching to balance memory and disk usage. It provides specialized utilities for filtering and analyzing large volumes of local data on a single machine. The system ensures data integrity through ACID-compliant transactions and multi-version concurrency co

redb is an embedded key-value store and ACID-compliant storage engine. It functions as a persistent storage system for saving and retrieving data as key-value pairs within a tree structure. The engine is built as an MVCC transactional database, utilizing multi-version concurrency control to manage simultaneous reads and writes without blocking. It employs a single-writer multi-reader model to ensure data consistency while allowing multiple threads to access the store. The system provides persistent state management and atomic transaction management to prevent data corruption during crashes.

Sled is an embedded key-value store and ACID-compliant database designed for high-performance data persistence. It functions as a log-structured storage engine that organizes data using B+ trees to support efficient range queries and prefix scans. The engine implements a zero-copy data store model, utilizing epoch-based reclamation to provide direct references to cached values without memory allocations. It distinguishes itself through a combination of write-ahead logging, page cache optimizations to reduce write amplification on flash storage, and serializable transactions for atomic multi-k

FASTER is a high-throughput key-value store that combines an in-memory data store with a hybrid memory-disk storage engine, enabling datasets larger than available RAM. It uses a latch-free, cache-optimized index for concurrent point lookups and heavy updates, and records all mutations to a persistent append-only log on disk with checksum validation and group-commit checkpointing for crash recovery. The system supports multi-key transactional workloads through atomic multi-key locking, ensuring transactional consistency without coarse-grained contention. It exposes the key-value store to remo