As of my last update in January 2022, OrientDB supports multiple storage engines, each optimized for different use cases and deployment scenarios. Here are the primary storage engines supported by OrientDB :
* Local Storage : Local storage engine is the default storage engine used by OrientDB. It stores data on the local disk of the server where the OrientDB instance is running. Local storage is suitable for single-server deployments and development environments where data durability and persistence are essential.
* PLocal (Persistent Local) Storage : PLocal storage engine is an improved version of the local storage engine with enhanced durability and crash recovery capabilities. It provides better performance and reliability by persisting data changes to disk asynchronously and maintaining transaction logs for crash recovery. PLocal storage is suitable for standalone and small-scale deployments where data durability and recovery are critical.
* Distributed Storage : Distributed storage engine is designed for distributed deployments of OrientDB across multiple nodes in a cluster. It enables data partitioning, replication, and distributed query processing to achieve horizontal scalability and fault tolerance. Distributed storage is suitable for large-scale deployments requiring high availability, scalability, and data distribution across multiple nodes.
* Memory Storage : Memory storage engine stores data entirely in-memory, offering ultra-fast read and write performance. However, data stored in memory is not persisted to disk and is lost upon server restart or shutdown. Memory storage is suitable for caching, temporary data storage, and applications requiring high-speed data access but can tolerate data loss.
* Local Paginated Storage : Local paginated storage engine is optimized for disk-based storage with improved efficiency and performance compared to traditional local storage. It stores data in paginated files on disk, reducing disk I/O and improving data access speed. Local paginated storage is suitable for applications with large datasets and disk-based storage requirements.
* Memory Paginated Storage : Memory paginated storage engine is similar to memory storage but stores data in paginated files on disk to reduce memory usage and improve performance. It combines the speed of in-memory storage with the durability of disk-based storage, making it suitable for applications requiring fast data access and data persistence.
Each storage engine in OrientDB offers unique features and trade-offs, allowing developers to choose the most suitable storage engine based on their specific requirements, deployment environment, and performance considerations. Additionally, OrientDB allows for custom storage engine implementations, enabling developers to extend and customize storage capabilities to meet their application needs.
