Actian Corporation controls the development of Ingres and makes certified binaries available for download, as well as providing worldwide support.

[3] During this time Ingres remained largely similar to IBM's seminal System R in concept; it differed in more permissive licensing of source code, in being based largely on DEC machines, both under UNIX[4] and VAX/VMS,[5] and in providing QUEL as a query language instead of SQL.

QUEL was considered at the time to run truer to Edgar F. Codd's relational algebra (especially concerning composability), but SQL was easier to parse and less intimidating for those without a formal background in mathematics.

Ingres began as a research project at the University of California, Berkeley, starting in the early 1970s and ending in 1985.

[3] The original code, like that from other projects at Berkeley, was available at minimal cost under a version of the BSD license.

It is ACID compatible and is fully transactional (including all DDL statements) and is part of the Lisog open-source stack initiative.

[8] Two scientists at Berkeley, Michael Stonebraker and Eugene Wong, became interested in the concept after reading the papers, and started a relational database research project of their own.

Stonebraker then introduced his idea to other agencies, and, with help from his colleagues he eventually obtained modest support from the NSF[12] and three military agencies: the Air Force Office of Scientific Research, the Army Research Office, and the Naval Electronic Systems Command.

Ingres went through an evolution similar to that of System R, with an early prototype in 1974 followed by major revisions to make the code maintainable.

Berkeley and other universities who used the Ingres source code worked on various commercial database software systems.

Berkeley students Jerry Held and later Karel Youseffi moved to Tandem Computers, where they built a database system that evolved into NonStop SQL.

One reason was Oracle's aggressive marketing; another was the increasing recognition of SQL as the preferred relational query language.

This relationship soured in the late 1990s, and today SQL Server outsells Sybase by a wide margin.

The most successful was a company named Relational Technology, Inc. (RTI), founded in 1980 by Stonebraker and Wong, and another Berkeley professor, Lawrence A.

They also developed a collection of front-end tools for creating and manipulating databases (e.g., reporterwriters, forms entry and update, etc.)

Over time, much of the source was rewritten to add functionality (for example, multiple-statement transactions, SQL, B-tree access method, date/time datatypes, etc.)

In addition to the low license fees, Ingres II had the advantage of lower resource requirements over Oracle, for example, which is why it could also be used on smaller machines.

Disadvantages were the more difficult usability, the lower number of platforms on which this system ran and fewer Ingres-capable applications.

On the grounds that the performance of Ingres was comparable to that of other large DBMS, Computer Associates raised the license fees sharply, thereby losing a key advantage over Oracle.

The code includes the DBMS server and utilities and the character-based front-end and application-development tools.

[29] In November 2010 Garnett & Helfrich Capital acquired the last 20% of equity in Ingres Corp that it did not already own.

Ingres is a disk-oriented DBMS, and by default employ the n-ary storage model (NSM),[41] also known as a row-store.

and Read Uncommitted, Serializable is the default isolation level and it provides the strongest consistency guarantee.

Nested-loop joins are most often seen on disjoint queries, where correlation variables and table names are arbitrarily used in random order.

Ingres supports: The Postgres project was started in the mid 1980s to address limitations of existing database-management implementations of the relational model.

The implementation also experimented with new interfaces between the database and application programs (e.g., "portals", which are sometimes referred to as "fat cursors").

[48] The resulting project, named "Postgres", aimed at introducing the minimum number of features needed to add complete types support.

In Postgres, the database "understood" relationships, and could retrieve information in related tables in a natural way using rules.