Oracle AI Database (commonly referred to as Oracle Database, Oracle DBMS, Oracle Autonomous Database, or simply as Oracle) is a proprietary multi-model database management system developed and marketed by Oracle Corporation. First released in 1979, it was among the earliest commercially available databases to use SQL.
It is commonly used for online transaction processing (OLTP), data warehousing (DW), and mixed database workloads. As a converged database, it supports multiple data models within a single engine, including relational, JSON document, XML, spatial, graph, text, and AI vector data, all queryable through SQL or APIs.
Oracle AI Database runs on-premises, on Oracle engineered systems such as Oracle Exadata, on Oracle Cloud Infrastructure, and as a managed Autonomous Database service. It is also offered inside Microsoft Azure, Google Cloud, and Amazon Web Services data centers through Oracle's multicloud offerings. The current long-term release is Oracle AI Database 26ai, which was introduced in October 2025.
History Larry Ellison and his two friends and former co-workers, Bob Miner and Ed Oates, started a consultancy called Software Development Laboratories (SDL) in 1977, later Oracle Corporation. SDL developed the original version of the Oracle software. The name Oracle comes from the code-name of a Central Intelligence Agency-funded project on which Ellison had worked while employed by Ampex; the CIA was Oracle's first customer, and allowed the company to use the code name for the new product.
Clustering, grid, and cloud computing Oracle Database 12c introduced multitenant architecture in 2013. Database In-Memory, including the In-Memory Column Store, was introduced in Oracle Database 12c Release 1 version 12.1.0.2. Oracle announced Oracle Autonomous Database in 2017, with the first services becoming available in 2018. Beyond the on-premises editions, Oracle Autonomous Database automates provisioning, tuning, patching, and scaling and is offered in data-warehousing and transaction-processing variants.
Architecture
Instances and databases An Oracle AI Database system consists of an instance and a database. The instance is a set of memory structures and background processes; the database is the set of files that store data. An instance exists only in memory, and in the multitenant configuration a single instance is associated with one container database. Client programs connect to the database through server processes, established by way of the Oracle Net listener.
Memory The principal memory structures are the System Global Area (SGA), shared by all server and background processes, and the Program Global Areas (PGA), which are private to individual processes. The shared pool, database buffer cache, and redo log buffer are components of the SGA, and the optional In-Memory Column Store also resides there. Each PGA holds session information and the work areas used to process SQL statements.
Processes Background processes operate on the database files and use the memory structures to do their work. They include the database writer, the log writer, the checkpoint process, the system monitor and process monitor processes, and the archiver processes that copy redo logs for recovery. Server processes handle connections from client programs and run their SQL statements.
Storage structures Storage is organized both logically and physically. Logically, data is held in tablespaces composed of segments, extents, and data blocks. Physically, the database comprises data files, control files, and online redo log files, with archived redo logs supporting media recovery. Data files can be placed on conventional file systems or managed by Automatic Storage Management (ASM), a volume manager and file system built into the database.
Multitenant architecture
Oracle Database 12c introduced the multitenant architecture, based on container databases (CDBs) and pluggable databases (PDBs). A CDB contains a root container (CDB$ROOT) that holds Oracle-supplied metadata and common users, a seed PDB (PDB$SEED) used as a template for creating new PDBs, and zero or more user-created PDBs. Beginning with Oracle Database 21c, the multitenant container database is the only supported architecture; earlier releases also supported non-container (non-CDB) databases. A PDB appears to a client or application as an independent database, while from the operating system's perspective the CDB is the database. Because PDBs are portable, they can be unplugged from one CDB and plugged into another, supporting database consolidation, cloning, and patching at the container level.
Concurrency and consistency
Oracle Database provides multiversion read consistency, also known as consistent read. When a transaction modifies data, the database writes the previous values to undo segments, allowing earlier versions of the same data to be read without blocking ongoing writes. In Oracle’s default read-committed isolation mode, each SQL statement sees only committed data, and that data is consistent as of a single point in time when the statement began; newly committed changes from other transactions are not incrementally exposed while the statement is running. Serializable and read-only transactions extend this behavior to transaction-level read consistency, so the transaction sees data as of the time the transaction began. This model allows queries to read a transactionally consistent snapshot without blocking concurrent updates; conflicting write operations may still block one another.
Data models Oracle AI Database is a converged, multi-model database: a single engine natively supports several data models and processes them using a common set of ACID transation properties, rather than relying on separate specialized systems. Independent reporting describes the engine as handling relational, JSON document, graph, spatial, and vector data together in one ACID-transactional engine, allowing these models to be combined without moving data between systems. The database-cataloging site DB-Engines likewise classifies Oracle as a multi-model system, listing document, graph, and spatial models alongside its primary relational model.
Oracle AI Database also supports native JSON data types that can be stored, indexed, and queried with SQL without requiring a predefined relational schema.
JSON Relational Duality, introduced in Oracle Database 23ai, lets the same data be accessed and updated either as relational tables or as JSON documents. Graph data models represent relationships between entities using nodes and edges, while spatial support enables the storage and querying of geographic and geometric information, including coordinates and shapes.
Relational data types Oracle AI Database includes traditional structured data stored in tables, using numeric, character, and date/time types. These form the basis of SQL-based data storage and querying and are used alongside other data models within the same database system.
High availability and scalability Oracle's database portfolio includes technologies for high availability, disaster recovery, replication, and scale-out deployment, including Oracle Real Application Clusters (RAC), Oracle Data Guard, Oracle GoldenGate, Oracle Flashback, Oracle Globally Distributed Database, and Oracle Exadata.
High availability and disaster recovery Oracle Real Application Clusters (Oracle RAC) is a shared-database clustering technology in which multiple database instances run on separate servers while accessing the same database. RAC was first released as part of Oracle 9.0.1 in 2001.
Oracle Data Guard protects a primary database by maintaining real-time standby copy(s) of the primary database that can be used for disaster recovery and role transitions such as switchover and failover. Active Data Guard extends this approach by allowing read-only workloads to run on a physical standby database while redo changes continue to be applied from the primary database.
Oracle GoldenGate is a replication product used for heterogeneous replication across different database platforms and vendors.
Oracle Flashback technologies provide point-in-time recovery features used to correct user-induced errors, including Flashback Query, Flashback Table, Flashback Drop, and Flashback Database.
Scalability Oracle Globally Distributed Database, formerly known as Oracle Sharding, distributes data from a single logical database across multiple independent databases, called shards, so that each shard stores part of the data and can run on separate resources. Oracle AI Database 26ai added RAFT-based replication for globally distributed database deployments, supporting higher availability and automatic failover across shards.
Oracle Exadata is an engineered database system that combines database servers with storage servers. Its Smart Scan storage-offload feature moves some processing, such as predicate filtering and column projection, from the database layer to the storage layer, reducing the volume of data returned to the database servers.
Performance Oracle Database includes features intended to improve query and transaction performance on large data sets, including Database In-Memory, partitioning, parallel execution, and compression.
The Database In-Memory feature adds an in-memory column store for selected database objects, allowing analytic queries to use a column-oriented in-memory representation, while the data can be stored in either transactional oriented row format or analytics oriented hybrid-columnar format.
Partitioning divides large tables and indexes into smaller physical pieces that remain a single logical object to applications. Each partition can be managed separately, and query performance can improve when the optimizer eliminates irrelevant partitions, a technique known as partition pruning.
For large operations, parallel execution can break a statement or other database task into smaller units that are processed concurrently, allowing the system to use more CPU and input/output resources than a serial execution plan.
Oracle Database also supports several table-compression methods. OLTP compression is intended for active tables, while Hybrid Columnar Compression reorganizes data into compression units and provides query and archive compression modes with higher compression ratios for less frequently updated data.
Security Oracle Database includes security features for encryption, auditing, and access control. A Common Criteria certification report for Oracle AI Database 26ai identified configurable audit capture, fine-grained access controls, user identification and authentication, and security management among the security functions of the evaluated target.
Transparent Data Encryption (TDE) encrypts database data below the SQL layer, with the database engine encrypting and decrypting data as it reads and writes it from the file system. Data redaction and masking features are used to reduce exposure of sensitive information in query results and applications.
For access control, Virtual Private Database (VPD) dynamically adds predicates to SQL statements against tables or views, allowing row and column restrictions to be enforced by database policies. Oracle Label Security provides label-based row-level access control on protected tables, and Oracle Database Vault adds mandatory access controls such as realms and command rules to restrict access to schemas, objects, and SQL operations, including by highly privileged users.
Oracle Database 23ai added security and privilege-management features including SQL Firewall, schema-level privileges, and enhanced data redaction and masking.