How do I set up ObjectBox in a Flutter project?

Start by adding the objectbox and objectbox_flutter_libs dependencies, annotate your Dart classes with @Entity, run the code generator, and initialize the store using openStore. The README provides a basic example and links to the Getting Started guide for detailed steps.

ObjectBox vs SQLite for Flutter: which is better?

ObjectBox is faster and offers a NoSQL, Dart-native API, making it superior for performance-critical and AI applications. SQLite is better if you need full SQL support, a wider ecosystem, and simpler setup without code generation.

Does ObjectBox support offline data sync?

Yes, ObjectBox Sync enables data synchronization across devices and servers both online and offline. However, this requires additional setup with the objectbox_sync_flutter_libs package and may involve licensing, as noted in the documentation.

How to perform vector search with ObjectBox for AI apps?

Use the on-device vector search capabilities by storing vectors as part of your objects and utilizing the vector query APIs. Refer to the official documentation on on-device ANN vector search for specific implementation examples and best practices.

Is ObjectBox free to use in commercial applications?

The core code is under the Apache License 2.0, but components like ObjectBox Sync may have different licenses. Check the ObjectBox website for details on commercial use, as the README mentions varying licenses for different components.

What are the main limitations of ObjectBox database?

Key limitations include the lack of advanced SQL features, dependency on code generation, and potential vendor lock-in. It's also primarily designed for Dart, so integration with other languages is limited compared to more universal databases.

Open-Awesome

ObjectBox

Apache-2.0Dartv5.3.1

A high-performance Flutter/Dart database for super-fast object persistence and on-device vector search.

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What is ObjectBox?

ObjectBox is a high-performance, NoSQL object database for Flutter and Dart applications, designed for super-fast persistence of Dart objects. It solves the need for efficient local data storage on mobile and IoT devices, reducing cloud costs and enabling offline functionality. Additionally, it introduces on-device vector search capabilities, making it suitable for AI-powered apps.

Target Audience

Flutter and Dart developers building cross-platform mobile, desktop, or IoT applications that require fast local data persistence, especially those integrating on-device AI features.

Value Proposition

Developers choose ObjectBox for its exceptional speed, intuitive Dart API that eliminates SQL complexity, and unique on-device vector database support for AI applications. Its built-in data sync and resource-efficient design make it a compelling alternative to SQLite and Firebase for offline-first and real-time apps.

Overview

Flutter database for super-fast Dart object persistence

Use Cases

Best For

Building Flutter apps that require fast local data storage without SQL
Developing on-device AI applications with vector search capabilities
Creating offline-first mobile applications with data synchronization
Building IoT and embedded applications with minimal resource consumption
Developing real-time applications that need high-performance database operations
Migrating from Firebase or SQLite to a more performant Dart-native solution

Not Ideal For

Projects that rely heavily on complex SQL queries, joins, and stored procedures, as ObjectBox's NoSQL model lacks advanced relational database features.
Teams developing applications in multiple programming languages beyond Dart, since ObjectBox is tightly integrated with the Dart ecosystem and not language-agnostic.
Scenarios where zero code generation and minimal setup are critical, due to ObjectBox's requirement for model annotation and generator tools.

Pros & Cons

Pros

Blazing Fast Performance

The README includes benchmarks showing ObjectBox outperforming SQLite and Hive in CRUD operations, making it ideal for real-time applications that demand high responsiveness.

Unique Vector Search

As the first on-device vector database for Dart, it enables AI-powered features like semantic search directly on mobile and IoT devices, reducing cloud dependency for AI apps.

Intuitive Dart API

Provides a statically typed, NoSQL interface that eliminates SQL complexity, with compile-time checks and optimizations, as shown in the example code for queries and CRUD operations.

Built-in Data Sync

Offers synchronization across devices and servers, both online and offline, serving as a self-hosted Firebase alternative for offline-first apps, mentioned in the features and sync packages.

Cons

Code Generation Overhead

Requires running a code generator for model classes, adding an extra build step and potential complexity, as indicated by the separate objectbox_generator package in the repository.

Vendor Lock-In Risks

As a proprietary solution from ObjectBox Ltd., migrating away can be difficult, and advanced features like sync may involve commercial licensing, hinted at in the license section and separate sync packages.

Limited Ecosystem Support

Compared to established databases like SQLite, ObjectBox has fewer third-party tools, community plugins, and integration options, which might slow down development or troubleshooting.

Open Source Alternative To

ObjectBox is an open-source alternative to the following products:

Firebase

Firebase is a Google-backed platform for developing mobile and web applications, providing backend services like authentication, databases, and hosting.

SQLite

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