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This is a comparison between notable database engines for the MySQL database management system (DBMS). A database engine (or "storage engine") is the underlying software component that a DBMS uses to create, read, update and delete (CRUD) data from a database.
Conversely, PostgreSQL has applied more of the specification implementing cross-table, cross-schema, and then left room for future cross-database functionality. MySQL aliases schema with database behind the scenes, such that CREATE SCHEMA and CREATE DATABASE are analogs. It can therefore be said that MySQL has implemented cross-database ...
Some - can only reverse engineer the entire database at once and drops any user modifications to the diagram (can't "refresh" the diagram to match the database) Forward engineering - the ability to update the database schema with changes made to its entities and relationships via the ER diagram visual designer Yes - can update user-selected ...
Proprietary, with a free-to-use edition (Polyhedra Lite) Relational (SQL, ODBC, JDBC) in-memory database system originally developed for use in SCADA and embedded systems, but used in a variety of other applications including financial systems. Supports data durability via snapshots and journal logging, and high availability via a hot-standby.
List of Relational Database Management Systems (Alphabetical Order) Name License 4th Dimension: Proprietary Access Database Engine (formerly known as Jet Database Engine) Proprietary Actian Zen (PSQL) (formerly known as Pervasive PSQL) Proprietary Adabas D: Proprietary Airtable: Proprietary Altibase: Proprietary Amazon Aurora: Proprietary ...
Database SQL Document Graph Object License Transactions ArangoDB: No: Yes: Yes: No: Business Source License 1.1: Full ACID, pessimistic locking, configurable durability
Comparison of multi-model databases; Comparison of MySQL database engines; O. Comparison of object database management systems;
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.