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IBM System R is a database system built as a research project at IBM's San Jose Research Laboratory beginning in 1974. [1] System R was a seminal project: it was the first implementation of SQL, which has since become the standard relational data query language.
Petri: deals with the assessment of, education in, and adoption of the Foundation's policies and procedures for collaborative development and the pros and cons of joining the Foundation; Phoenix: SQL layer on HBase; Pig: a platform for analyzing large data sets on Hadoop; Pinot: a column-oriented, open-source, distributed data store written in ...
an overall enterprise architecture that favors shared data models [5] over allowing each application to have its own, idiosyncratic data model. Even an extreme database-centric architecture called RDBMS-only architecture [6] [7] has been proposed, in which the three classic layers of an application are kept within the RDBMS. This architecture ...
Presto (including PrestoDB, and PrestoSQL which was re-branded to Trino) is a distributed query engine for big data using the SQL query language. Its architecture allows users to query data sources such as Hadoop, Cassandra, Kafka, AWS S3, Alluxio, MySQL, MongoDB and Teradata, [1] and allows use of multiple data sources within a query.
SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce after learning about the relational model from Edgar F. Codd [12] in the early 1970s. [13] This version, initially called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM's original quasirelational database management system, System R, which a group at IBM San ...
The OS 2200 database managers are all part of the Universal Data System (UDS). UDS provides a common control structure for multiple different data models. Flat files (sequential, multi-keyed indexed sequential, MSAM, and fixed-block), [1] network, [2] and relational [3] data models all share a common locking, recovery, and clustering mechanism.
A database shard, or simply a shard, is a horizontal partition of data in a database or search engine. Each shard may be held on a separate database server instance, to spread load. Some data in a database remains present in all shards, [a] but some appears only in a single shard. Each shard acts as the single source for this subset of data.
Database scalability is the ability of a database to handle changing demands by adding/removing resources. Databases use a host of techniques to cope. [ 1 ] According to Marc Brooker: "a system is scalable in the range where marginal cost of additional workload is nearly constant."