OrientDB uses various storage formats to persist data efficiently on disk, depending on the storage engine and configuration. Here are the primary storage formats used by OrientDB:
* Record Storage : Record storage is the fundamental storage format used by OrientDB to store data records, including documents, vertices, edges, and index entries. Records are serialized and stored in binary format on disk. Each record is assigned a unique Record ID (RID) that serves as a reference for accessing and manipulating the record.
* Page Storage : Page storage is used by disk-based storage engines to organize data into fixed-size pages or blocks. Pages are the basic unit of data storage and retrieval in OrientDB's paginated storage engines. Data records are stored in pages, and pages are managed and manipulated by the storage engine to optimize disk I/O and memory usage.
* Segment Storage : Segment storage is used by OrientDB's distributed storage engine to partition and distribute data across multiple nodes in a cluster. Segments are logical units of data partitioning that contain a subset of the dataset. Each segment is stored as a separate file or data structure on disk and is replicated across multiple nodes for fault tolerance.
* Transaction Log : Transaction log is a sequential log file used by OrientDB to record changes made to the database during transaction execution. The transaction log captures transactional operations, such as insertions, updates, deletions, and index changes, in a serialized format. The transaction log is essential for ensuring data durability, atomicity, and crash recovery in OrientDB.
* Index Files : Index files store index entries and metadata for maintaining indexes on database fields. OrientDB supports various index types, including B-tree indexes, hash indexes, full-text indexes, and spatial indexes. Index files are used to accelerate data retrieval and querying by enabling fast lookup and retrieval of records based on indexed fields.
* Cluster Files : Cluster files are used by OrientDB's distributed storage engine to store data partitions or shards within a distributed database cluster. Each cluster file contains data records belonging to a specific shard or partition of the dataset. Cluster files are replicated and distributed across multiple nodes in the cluster to achieve fault tolerance and data redundancy.
These storage formats collectively enable OrientDB to efficiently persist, manage, and retrieve data on disk while providing features such as data durability, fault tolerance, and transactional consistency. The choice of storage format depends on the storage engine, deployment requirements, and performance considerations of the OrientDB database instance.
