DBMS > Drizzle vs. Hive vs. IBM Db2 Event Store
System Properties Comparison Drizzle vs. Hive vs. IBM Db2 Event Store
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|Editorial information provided by DB-Engines|
|Name||Drizzle Xexclude from comparison||Hive Xexclude from comparison||IBM Db2 Event Store Xexclude from comparison|
|Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.|
|Description||MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.||data warehouse software for querying and managing large distributed datasets, built on Hadoop||Distributed Event Store optimized for Internet of Things use cases|
|Primary database model||Relational DBMS||Relational DBMS||Event Store|
Time Series DBMS
|Developer||Drizzle project, originally started by Brian Aker||Apache Software Foundation initially developed by Facebook||IBM|
|Current release||7.2.4, September 2012||3.1.3, April 2022||2.0|
|License Commercial or Open Source||Open Source GNU GPL||Open Source Apache Version 2||commercial free developer edition available|
|Cloud-based only Only available as a cloud service||no||no||no|
|DBaaS offerings (sponsored links) Database as a Service|
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|Implementation language||C++||Java||C and C++|
|Server operating systems||FreeBSD|
|All OS with a Java VM||Linux Linux, macOS, Windows for the developer addition|
|Typing predefined data types such as float or date||yes||yes||yes|
|XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.||no|
|SQL Support of SQL||yes with proprietary extensions||SQL-like DML and DDL statements||yes through the embedded Spark runtime|
|APIs and other access methods||JDBC||JDBC|
RESTful HTTP API
|Supported programming languages||C|
|Server-side scripts Stored procedures||no||yes user defined functions and integration of map-reduce||yes|
|Triggers||no hooks for callbacks inside the server can be used.||no||no|
|Partitioning methods Methods for storing different data on different nodes||Sharding||Sharding||Sharding|
|Replication methods Methods for redundantly storing data on multiple nodes||Multi-source replication|
|selectable replication factor||Active-active shard replication|
|MapReduce Offers an API for user-defined Map/Reduce methods||no||yes query execution via MapReduce||no|
|Consistency concepts Methods to ensure consistency in a distributed system||Eventual Consistency||Eventual Consistency|
|Foreign keys Referential integrity||yes||no||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID||no||no|
|Concurrency Support for concurrent manipulation of data||yes||yes||No - written data is immutable|
|Durability Support for making data persistent||yes||yes||Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||yes|
|User concepts Access control||Pluggable authentication mechanisms e.g. LDAP, HTTP||Access rights for users, groups and roles||fine grained access rights according to SQL-standard|
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|Drizzle||Hive||IBM Db2 Event Store|
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