OrientDB is an open source NoSQL database management system written in Java. It is a Multi-model database, supporting graph, document, key/value, and object models, but the relationships are managed as in graph databases with direct connections between records. It supports schema-less, schema-full and schema-mixed modes. It has a strong security profiling system based on users and roles and supports querying with Gremlin along with SQL extended for graph traversal. OrientDB uses several indexing mechanisms based on B-tree and Extendible hashing, the last one is known as "hash index", there are plans to implement LSM-tree and Fractal tree index based indexes. Each record has Surrogate key which indicates position of record inside of Array list , links between records are stored either as single value of record's position stored inside of referrer or as B-tree of record positions (so-called record IDs or RIDs) which allows fast traversal (with O(1) complexity) of one-to-many relationships and fast addition/removal of new links. OrientDB is the fifth most popular graph database according to the DB-Engines graph database ranking, as of December 2021.
The development of OrientDB still relies on an open source community led by OrientDB LTD company created by its original author Luca Garulli. The project uses GitHub to manage the sources, contributors and versioning, Google Group and Stack Overflow to provide free support to the worldwide users. OrientDB also offers a free Udemy course for those hoping to learn the basics and get started with OrientDB.
OrientDB is built with a multi-model graph/document engine. OrientDB feels like a graph database first, but there's no reason the key-value store can't be used on its own. While OrientDB includes a SQL layer, the support for edges effectively means that these may be used to traverse relationships rather than employing a JOIN statement. OrientDB handles every record / document as an object and the linking between objects / documents is not through references, it's direct linking (saving a pointer to the object).
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In the field of database design, a multi-model database is a database management system designed to support multiple data models against a single, integrated backend. In contrast, most database management systems are organized around a single data model that determines how data can be organized, stored, and manipulated. Document, graph, relational, and key–value models are examples of data models that may be supported by a multi-model database. The relational data model became popular after its publication by Edgar F.
A graph database (GDB) is a database that uses graph structures for semantic queries with nodes, edges, and properties to represent and store data. A key concept of the system is the graph (or edge or relationship). The graph relates the data items in the store to a collection of nodes and edges, the edges representing the relationships between the nodes. The relationships allow data in the store to be linked together directly and, in many cases, retrieved with one operation.
A key–value database, or key–value store, is a data storage paradigm designed for storing, retrieving, and managing associative arrays, and a data structure more commonly known today as a dictionary or hash table. Dictionaries contain a collection of objects, or records, which in turn have many different fields within them, each containing data. These records are stored and retrieved using a key that uniquely identifies the record, and is used to find the data within the database.