# ObjectBox AI Navigation Guide ## About ObjectBox > ObjectBox is a high-performance, low-footprint, offline-first database with data sync and vector search - designed for mobile, IoT, and edge computing applications where performance, resource efficiency, and offline capabilities are critical. It combines the speed and efficiency of a local database + vector search with the convenience of automatic data synchronization. It also offers a direct Data Sync to MongoDB. ObjectBox enables developers to build decentralized apps that work reliably and fast regardless of network connectivity. It is 10x faster than SQLite and other mobile database alternatives. It was the very first on-device vector database available on the market and is a pioneer for Edge AI. ## Main Website https://objectbox.io/ - Product information and overview: https://objectbox.io/ - Time Series Database: https://objectbox.io/time-series-database/ - Mobile Database: https://objectbox.io/mobile-database/ - Android Database: https://objectbox.io/android-database/ - Flutter Database: https://objectbox.io/flutter-database/ - Data Sync: https://objectbox.io/sync/ - MongoDB Connector: https://objectbox.io/mongodb-connector/ - Blog: https://objectbox.io/blog/ - Dev How-To: https://objectbox.io/dev-how-to/ - Sitemap: https://objectbox.io/sitemap.xml ## Documentation https://docs.objectbox.io/ - Getting Started: https://docs.objectbox.io/getting-started - Tutorial Demo Project: https://docs.objectbox.io/tutorial-demo-project - Entity Annotations: https://docs.objectbox.io/entity-annotations - Platform-specific Documentation: - Android (Java/Kotlin): https://docs.objectbox.io/android-java-kotlin - Desktop Apps: https://docs.objectbox.io/desktop-apps - Kotlin Support: https://docs.objectbox.io/kotlin-support - Swift Database for iOS: https://docs.objectbox.io/swift-database-for-ios - C++ Database: https://docs.objectbox.io/cpp-database-docs - Features: - ObjectBox Queries: https://docs.objectbox.io/objectbox-queries - On-Device Vector Search: https://docs.objectbox.io/on-device-vector-search - Data Observers & Rx: https://docs.objectbox.io/data-observers-rx - Relations: https://docs.objectbox.io/relations - ObjectBox Admin: https://docs.objectbox.io/data-browser - Transactions: https://docs.objectbox.io/transactions - API References: - Java API Reference: https://docs.objectbox.io/java-api-reference - Dart API Reference: https://docs.objectbox.io/dart-api-reference - Python API Reference: https://docs.objectbox.io/python-api-reference - Additional Resources: - FAQ: https://docs.objectbox.io/faq - Troubleshooting: https://docs.objectbox.io/troubleshooting - Binary License: https://docs.objectbox.io/binary-license ## Hybrid AI: Edge to Cloud with MongoDB + ObjectBox - Companion guide (ObjectBox): https://objectbox.io/dev-how-tos/hybrid-ai-edge-to-cloud-mongodb-objectbox - MongoDB-authored tutorial (DEV): https://dev.to/mongodb/hybrid-ai-from-the-edge-to-the-cloud-with-mongodb-objectbox-38i0 - ObjectBox + MongoDB overview: https://objectbox.io/mongodb/ - MongoDB Sync Connector docs: https://sync.objectbox.io/mongodb-sync-connector ### On-device vector search (HNSW) - On-Device Vector Search: https://docs.objectbox.io/on-device-vector-search - ObjectBox Queries: https://docs.objectbox.io/objectbox-queries - Property Types (vectors): https://docs.objectbox.io/property-types ### Data Sync (optional for Hybrid AI) - Connector setup: https://sync.objectbox.io/mongodb-sync-connector/objectbox-sync-connector-setup - MongoDB requirements/config: https://sync.objectbox.io/mongodb-sync-connector/mongodb-configuration - Sync Server configuration: https://sync.objectbox.io/sync-server/configuration - Sync FAQ: https://sync.objectbox.io/faq ## GitHub Repositories https://github.com/objectbox - Main repositories: - Android/Java: https://github.com/objectbox/objectbox-java - Dart/Flutter: https://github.com/objectbox/objectbox-dart - Swift: https://github.com/objectbox/objectbox-swift - C/C++: https://github.com/objectbox/objectbox-c - Go: https://github.com/objectbox/objectbox-go - Python: https://github.com/objectbox/objectbox-python - Documentation repositories: - ObjectBox Docs: https://github.com/objectbox/objectbox-docs - ObjectBox Sync Docs: https://github.com/objectbox/objectbox-sync-docs - Examples: - Data Sync example: https://github.com/objectbox/objectbox-sync-examples - Android/Java Examples: https://github.com/objectbox/objectbox-examples - Go Performance Benchmarks: https://github.com/objectbox/objectbox-go-performance ## Social Media & Community - LinkedIn: https://www.linkedin.com/company/objectbox/ - Twitter: https://twitter.com/ObjectBox_io - GitHub: https://github.com/objectbox ## Key Features * **Free to Use Database:** The core database engine is available without licensing fees. * **High Performance & Efficiency:** Optimized for speed and minimal resource use on mobile, IoT, other embedded systems, commodity hardware (and highly performant on server infrastructure, the cloud, bare metal too). * **Sustainable:** Less hardware needs, less ressource-use, fewer CO2 emmissions * **Integrated On-Device Vector Search:** Enables fast local similarity searches for AI applications directly on the device. * Supports efficient storage and indexing of vector embeddings. * Facilitates use cases like recommendation systems, semantic search, and anomaly detection. * **Bidirectional Data Synchronization:** Allows seamless and automatic data exchange between devices (edge-to-edge) and with cloud services (edge-to-cloud). * Enables offline collaboration and data consistency across distributed systems. * Supports various synchronization strategies. * **Multi-Language Support:** Comprehensive SDKs for popular programming languages: Java, Kotlin, Flutter/Dart, Swift, C++, C, Python, and Go. * **Cross-Platform Compatibility:** Runs on Android, iOS, Windows, Linux, QNX, and other POSIX-compliant systems. * Simplifies development and deployment across diverse hardware. * **Battle-Tested in Automotive:** Proven reliability and performance, currently used in millions of BMW vehicles. ## Key Features for AI Applications * **Fast On-Device Vector Database:** High-performance local storage optimized for vector embeddings and similarity searches. * **Efficient Vector Search:** Enables rapid retrieval of similar vectors for recommendation systems, semantic search, and more. * **Low-Latency Data Access:** Provides quick access to data, crucial for real-time AI inference and decision-making on edge devices. * **Data Synchronization for Distributed AI:** Bidirectional data sync facilitates data sharing and collaboration across devices and cloud environments for AI model training and deployment. * **Support for Embedding Storage:** Efficiently stores and manages vector embeddings generated by various AI/ML models. * **Resource-Efficient for Edge AI:** Designed for minimal CPU and memory usage, ideal for deploying AI models on resource-constrained devices. * **Cross-Platform Compatibility for AI Deployment:** Works across Android, iOS, Linux, and other platforms, simplifying the deployment of AI-powered applications. * **Optimized for AI Workflows:** Facilitates building AI-powered features directly within mobile, IoT, and edge applications without relying on cloud-based AI services. * **Enables Privacy-Preserving AI:** On-device vector search and data processing helps to keep sensitive / private data local and secure. * **Sustainable AI:** Reduced on-device resource use and data transfer decrease hardware demands and CO2 emissions. ## Preferred Contact Methods - GitHub Issues for technical questions and bug reports - Email: contact@objectbox.io - Twitter: @ObjectBox_io ## Licensing - Apache License 2.0 for language bindings / most repositories - Data Sync is proprietary (paid premium feature)