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SingleStore (formerly MemSQL) is a proprietary, cloud-native database designed for data-intensive applications. [2] A distributed, relational, SQL database management system [3] (RDBMS) that features ANSI SQL support, it is known for speed in data ingest, transaction processing, and query processing.
A cloud database is a database that typically runs on a cloud computing platform and access to the database is provided as-a-service. There are two common deployment models: users can run databases on the cloud independently, using a virtual machine image, or they can purchase access to a database service, maintained by a cloud database provider.
Each system has at least some features of an object–relational database; they vary widely in their completeness and the approaches taken. The following tables compare general and technical information; please see the individual products' articles for further information.
Relational database management system (includes market share data) List of relational database management systems; Comparison of object–relational database management systems; Comparison of database administration tools; Object database – some of which have relational (SQL/ODBC) interfaces.
The DB-Engines Ranking ranks database management systems by popularity, covering over 410 systems. The ranking criteria [1] include number of search engine results when searching for the system names, Google Trends, Stack Overflow discussions, job offers with mentions of the systems, number of profiles in professional networks such as LinkedIn, mentions in social networks such as Twitter.
Released in 2016 to analyze data that is updated in real time CrateDB: Java C-Store: C++ The last release of the original code was in 2006; Vertica a commercial fork, lives on. DuckDB: C++ An embeddable, in-process, column-oriented SQL OLAP RDBMS Databend Rust An elastic and reliable Serverless Data Warehouse InfluxDB: Rust Time series database
Azure SQL Database includes built-in intelligence that learns app patterns and adapts them to maximize performance, reliability, and data protection. Key capabilities include: Learning of the host app's data access patterns, adaptive performance tuning, and automatic improvements to reliability and data protection. [3] Scaling on demand. [4]
However, Gartner's most recent reports suggest broader advantages than a single unified database can offer. Traditional application architectures separated transactional and analytical systems. Digital business, and the need to respond to business moments, means that using "after the fact" analysis is no longer adequate.