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An increasing number of application scenarios has exacerbated database fragmentation, making database architecture, protocols, functions, and application scenarios increasingly diversified. In terms of database architecture, the centralized database which is evolved from a single-machine system coexists with the new generation of native distributed databases. In terms of database protocols, MySQL and PostgreSQL, two major open source ecosystems, as well as the service ecosystems provided by depending vendors, also have a foothold in the global database system.
An increasing number of application scenarios has exacerbated database fragmentation, making database architecture, protocols, functions, and application scenarios increasingly diversified. In terms of database architecture, the centralized database which is evolved from a single-machine system coexists with the new generation of native distributed databases. In terms of database protocols, MySQL and PostgreSQL, two major open source ecosystems, as well as the service ecosystems provided by depending vendors, also have a foothold in the global database system.
Today, it is normal for enterprises to leverage diversified databases. In my market of expertise, China, in the Internet industry, MySQL together with data sharding middleware is the go to architecture, with GreenPlum, HBase, Elasticsearch, Clickhouse and other big data ecosystems being auxiliary computing engine for analytical data. At the same time, some legacy systems (such as SQLServer legacy from .NET transformation, or Oracle legacy from outsourcing) can still be found in use. In the financial industry, Oracle or DB2 is still heavily used as the core transaction system. New business is migrating to MySQL or PostgreSQL. In addition to transactional databases, analytical databases are increasingly diversified as well.
Today, it is normal for enterprises to leverage diversified databases. In my market of expertise, China, in the Internet industry, MySQL together with data sharding middleware is the go to architecture, with GreenPlum, HBase, Elasticsearch, Clickhouse and other big data ecosystems being auxiliary computing engine for analytical data. At the same time, some legacy systems (such as SQLServer legacy from .NET transformation, or Oracle legacy from outsourcing) can still be found in use. In the financial industry, Oracle or DB2 is still heavily used as the core transaction system. New business is migrating to MySQL or PostgreSQL. In addition to transactional databases, analytical databases are increasingly diversified as well.
Today, it is normal for enterprises to leverage diversified databases. In my market of expertise, China, in the Internet industry, MySQL together with data sharding middleware is the go to architecture, with GreenPlum, HBase, Elasticsearch, Clickhouse and other big data ecosystems being auxiliary computing engine for analytical data. At the same time, some legacy systems (such as SQLServer legacy from .NET transformation, or Oracle legacy from outsourcing) can still be found in use. In the financial industry, Oracle or DB2 is still heavily used as the core transaction system. New business is migrating to MySQL or PostgreSQL. In addition to transactional databases, analytical databases are increasingly diversified as well.