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DBMS > Drizzle vs. Hive vs. JaguarDB vs. Kinetica vs. Microsoft Azure Table Storage

System Properties Comparison Drizzle vs. Hive vs. JaguarDB vs. Kinetica vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonHive  Xexclude from comparisonJaguarDB  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Table Storage  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.
DescriptionMySQL 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 HadoopPerformant, highly scalable DBMS for AI and IoT applicationsFully vectorized database across both GPUs and CPUsA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSRelational DBMSKey-value store
Vector DBMS
Relational DBMSWide column store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score0.09
Rank#356  Overall
#53  Key-value stores
#13  Vector DBMS
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score4.92
Rank#73  Overall
#6  Wide column stores
Websitehive.apache.orgwww.jaguardb.comwww.kinetica.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homewww.jaguardb.com/­support.htmldocs.kinetica.com
DeveloperDrizzle project, originally started by Brian AkerApache Software Foundation infoinitially developed by FacebookDataJaguar, Inc.KineticaMicrosoft
Initial release20082012201520122012
Current release7.2.4, September 20123.1.3, April 20223.3 July 20237.1, August 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache Version 2Open Source infoGPL V3.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++ infothe server part. Clients available in other languagesC, C++
Server operating systemsFreeBSD
Linux
OS X
All OS with a Java VMLinuxLinuxhosted
Data schemeyesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like DML and DDL statementsA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersSQL-like DML and DDL statementsno
APIs and other access methodsJDBCJDBC
ODBC
Thrift
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
C++
Java
PHP
Python
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reducenouser defined functionsno
Triggersno infohooks for callbacks inside the server can be used.nonoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factorMulti-source replicationSource-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMno
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and rolesrights management via user accountsAccess rights for users and roles on table levelAccess rights based on private key authentication or shared access signatures

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More resources
DrizzleHiveJaguarDBKineticaMicrosoft Azure Table Storage
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