Oracle Database 23ai has been updated with new features to support AI-based application development and other tasks. Oracle is making the latest long-term support release version of its database offering — Database 23c — generally available for enterprises under the name Oracle Database 23ai. The change in nomenclature can be attributed to the addition of new features to the database that are expected to help with AI-based application development among other tasks, the company said. [ Related: Oracle CloudWorld 2024 coverage ] Database 23c, showcased for the first time at the company’s annual event in 2022, was released to developers in early 2023 before being released to enterprises, marking a shift in the company’s tradition for the first time. Stiff competition from database rivals forced Oracle to shift its strategy for its databases business in favor of developers, who could offer the company a much-needed impetus for growth. In September last year, Oracle said it was working on adding vector search capabilities to Database 23c at its annual CloudWorld conference. These capabilities, dubbed AI Vector Search, included a new vector data type, vector indexes, and vector search SQL operators that enable the Oracle Database to store the semantic content of documents, images, and other unstructured data as vectors, and use these to run fast similarity queries, the company said. AI Vector Search in Database 23c that has been passed onto 23ai along with other features, according to the company, also supports retrieval-augmented generation (RAG), a generative AI technique, that combines large language models (LLMs) and private business data to deliver responses to natural language questions. Other notable features of Database 23c that have been passed onto 23ai include JSON Relational Duality, which unifies the relational and document data models, SQL support for Graph queries directly on OLTP data, and stored procedures in JavaScript, allowing developers to build applications in either relational or JSON paradigms. Database 23ai, according to Oracle, will be available as a cloud service as well as on-premises through a variety of offerings, including Oracle Exadata Database Service, Oracle Exadata Cloud@Customer, and Oracle Base Database Service, as well as on Oracle Database@Azure. While Oracle did not release Database 23ai’s pricing, the developer version of Database 23c continues to be free since its release. The reason to offer Database 23c for free can be attributed to the company’s strategy to lower the barriers to the adoption of its database as rival database providers also add newer features, such as vector search, to support AI workloads. Several database vendors, such as MongoDB, AWS, Google Cloud, Microsoft, Zilliz, DataStax, Pinecone, Couchbase, Snowflake, and SingleStore, have all added capabilities to support AI-based tasks. Vector databases and vector search are two technologies that developers use to convert unstructured information into vectors, now more commonly called embeddings. These embeddings, in turn, make storing, searching, and comparing the information easier, faster, and significantly more scalable for large datasets. Related content news SingleStore acquires BryteFlow to boost data ingestion capabilities SingleStore will integrate BryteFlow’s capabilties inside its database offering via a no-code interface named SingleConnect. By Anirban Ghoshal Oct 03, 2024 4 mins ETL Databases Data Integration feature 3 great new features in Postgres 17 Highly optimized incremental backups, expanded SQL/JSON support, and a configurable SLRU cache are three of the most impactful new features in the latest PostgreSQL release. By Tom Kincaid Sep 26, 2024 6 mins PostgreSQL Relational Databases Databases feature Why vector databases aren’t just databases Vector databases don’t just store your data. They find the most meaningful connections within it, driving insights and decisions at scale. By David Myriel Sep 23, 2024 5 mins Generative AI Databases Artificial Intelligence feature Overcoming AI hallucinations with RAG and knowledge graphs Combining knowledge graphs with retrieval-augmented generation can improve the accuracy of your generative AI application, and generally can be done using your existing database. By Dom Couldwell Sep 17, 2024 6 mins Graph Databases Generative AI Databases Resources Videos