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objectbox/objectbox-java

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Objectbox Java

ObjectBox Java is an embedded NoSQL object database for Java and Android that stores data objects directly without relational mapping. It functions as a native-process storage engine, allowing applications to persist plain Java or Kotlin classes as entities.

The project distinguishes itself with an on-device vector database capability, utilizing HNSW indexes to perform approximate nearest neighbor searches and semantic similarity queries. It also includes a locally hosted web-based browser for visualizing data objects, schemas, and dependency diagrams.

The database covers a broad range of data management capabilities, including ACID-compliant atomic transactions, reactive data streams for real-time observations, and cross-platform data synchronization. Its storage surface supports object-relation mapping with lazy loading, property-based filtering, and the ability to initialize the data store in memory for caching or automated testing.

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objectbox.io
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Features

  • Embedded Database Engines - Functions as a native-process embedded database engine that runs directly within the application to eliminate network latency.
  • Object-Oriented Databases - Provides an embedded object-oriented database that stores Java and Kotlin classes directly without relational mapping.
  • Object-Relational Mapping - Stores Java or Kotlin classes as database entities, eliminating the need for relational mapping tables.
  • Collection Querying - Retrieves objects from the database using equality or range filters and applies specific sort orders.
  • Mobile Storage Engines - Provides a high-performance embedded storage engine optimized for mobile and JVM environments.
  • Atomic Transactions - Wraps multiple data operations into single atomic units to ensure ACID consistency.
  • Embedded Local Storage - Saves application objects directly to a local database on Android or JVM for fast offline access.
  • NoSQL Databases - Implements a non-relational object store for persisting plain Java classes as entities.
  • Object Storage Database Engines - Acts as an object storage engine that runs in-process for high-performance local data persistence.
  • Object Property Filtering - Retrieves specific result sets by applying property conditions and logical operators to stored objects.
  • Filtered and Ordered Queries - Sorts returned objects based on specific properties with configurable direction and null handling.
  • ACID-Compliant - Provides ACID-compliant atomic transactions to ensure data consistency and prevent partial updates during storage operations.
  • Entity Property Queries - Retrieves and manages stored entities using a dedicated interface tailored to specific object types.
  • HNSW Indexes - Implements HNSW indexes to enable high-performance approximate nearest neighbor searches for vector embeddings.
  • On-Device Vector Databases - Provides a local vector database utilizing HNSW indexes for on-device approximate nearest neighbor searches.
  • Vector Search - Performs approximate nearest neighbor searches and semantic similarity queries using HNSW indexes on-device.
  • Semantic Vector Search - Enables retrieval of objects based on the mathematical distance between query and document embeddings.
  • Binary Serialization Formats - Utilizes a compact binary serialization format to efficiently persist primitives and complex collections on-device.
  • Cross-Client Data Synchronization - Synchronizes objects between on-device storage and other platforms to maintain data consistency.
  • In-Memory Data Stores - Supports an in-memory storage mode for high-speed data access during caching or automated testing.
  • Data Change Observers - Offers reactive data observation to notify applications of database changes in real time.
  • Asynchronous Transaction APIs - Executes database transactions on separate threads to avoid blocking the main application execution.
  • Entity Modeling - Supports structured data modeling in Kotlin using standard classes and sealed subclasses for inheritance.
  • Automatic Persistence - Automatically maps application classes to database entities to handle the persistence of new objects.
  • In-Memory Databases - Supports initializing the data store in RAM for high-speed caching and automated testing.
  • Lazy-Loaded Object Relations - Provides lazy-loaded one-to-one relations using proxies to optimize initial query time and memory.
  • Object Relation Lazy Loading - Implements proxy-based lazy loading to minimize memory usage by retrieving related objects only upon first access.
  • Object Identifier Management - Manages unique integer identifiers for objects to facilitate precise referencing and retrieval of data.
  • Embedded Collection Persistence - Persists lists and arrays of fixed-type values and binary blobs directly within a data object.
  • Object-Relational Mapping Associations - Links objects via integer references to establish one-to-one and one-to-many associations between entities.
  • Reactive Data Streams - Converts database subscriptions into asynchronous data streams to drive reactive user interface updates.
  • Entity Associations - Enables the definition of associations and dependencies between data entities using variable properties.
  • Database Object Browsers - Ships a locally hosted web browser for visualizing data objects, schemas, and dependency diagrams.
  • Database Change Notifications - Provides triggers and observers that notify the application when specific database objects are modified.
  • Persistence - Superfast object-oriented database.
4,612 stars·307 forks·Java·Apache-2.0·39 views

Star history

Star history chart for objectbox/objectbox-javaStar history chart for objectbox/objectbox-java

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

Frequently asked questions

What does objectbox/objectbox-java do?

ObjectBox Java is an embedded NoSQL object database for Java and Android that stores data objects directly without relational mapping. It functions as a native-process storage engine, allowing applications to persist plain Java or Kotlin classes as entities.

What are the main features of objectbox/objectbox-java?

The main features of objectbox/objectbox-java are: Embedded Database Engines, Object-Oriented Databases, Object-Relational Mapping, Collection Querying, Mobile Storage Engines, Atomic Transactions, Embedded Local Storage, NoSQL Databases.

Which projects share features with objectbox/objectbox-java?

Projects with overlapping indexed features include: realm/realm-swift — This is a mobile object database and NoSQL local data store that replaces relational tables with a schema-based model.… dotnet/efcore — Entity Framework Core is an object-relational mapper that enables developers to interact with database systems using… mongodb/mongo-python-driver — The MongoDB Python Driver is a client library and NoSQL database client used to execute CRUD operations and manage… memgraph/memgraph — Memgraph is an in-memory, distributed graph database designed for high-performance labeled property graph management.… vincit/objection.js — Objection.js is an object-relational mapper for Node.js that maps SQL database tables to classes and rows to model… dotnetcore/freesql — FreeSql is a .NET object-relational mapper and data access layer that translates object-oriented code into SQL for…

Projects sharing features with Objectbox Java

These projects share indexed features with Objectbox Java. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • realm/realm-swiftrealm avatar

    realm/realm-swift

    16,608View on GitHub↗

    This is a mobile object database and NoSQL local data store that replaces relational tables with a schema-based model. It functions as a reactive data store, using live object observations and change notifications to trigger automatic user interface refreshes. The system provides built-in mobile cloud data synchronization to keep local datasets consistent with a remote server across multiple devices. It also includes security features for encrypted local storage, protecting sensitive on-disk data using at-rest encryption keys and fine-grained access control. Broad capabilities include object

    Objective-C
    View on GitHub↗16,608
  • dotnet/efcoredotnet avatar

    dotnet/efcore

    14,587View on GitHub↗

    Entity Framework Core is an object-relational mapper that enables developers to interact with database systems using strongly-typed code. It serves as a comprehensive data access framework, providing a unified interface for mapping application objects to relational and non-relational database schemas while managing the lifecycle of data operations through a central context. The project distinguishes itself through a provider-based architecture that decouples core data access logic from specific database engines, allowing for consistent interaction across diverse storage systems. It features a

    C#aspnet-productc-sharpdatabase
    View on GitHub↗14,587
  • mongodb/mongo-python-drivermongodb avatar

    mongodb/mongo-python-driver

    4,342View on GitHub↗

    The MongoDB Python Driver is a client library and NoSQL database client used to execute CRUD operations and manage data within MongoDB databases using the Python programming language. It serves as a database connectivity library that handles authentication and connection pooling, while also providing a vector search client for managing embedding indexes and retrieving data based on semantic similarity. The driver supports both synchronous and asynchronous database driver models to perform non-blocking I/O operations and stream data from database clusters. It distinguishes itself through speci

    Pythonmongodbmongodb-driverpymongo
    View on GitHub↗4,342
  • memgraph/memgraphmemgraph avatar

    memgraph/memgraph

    4,163View on GitHub↗

    Memgraph is an in-memory, distributed graph database designed for high-performance labeled property graph management. It utilizes a Cypher query engine for declarative data retrieval and manipulation, providing a scalable knowledge graph backend that integrates vector search and graph traversals. The system distinguishes itself as a real-time graph analytics platform, employing native C++ and CUDA implementations to execute complex network analysis and dynamic community detection on streaming data. It provides specialized support for AI integration, including GraphRAG capabilities, the constr

    C++cyphergraphgraph-algorithms
    View on GitHub↗4,163
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