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DBMS > Hive vs. Kinetica vs. Oracle Berkeley DB vs. Vitess

System Properties Comparison Hive vs. Kinetica vs. Oracle Berkeley DB vs. Vitess

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonKinetica  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonVitess  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopFully vectorized database across both GPUs and CPUsWidely used in-process key-value storeScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitehive.apache.orgwww.kinetica.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlvitess.io
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.kinetica.comdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlvitess.io/­docs
DeveloperApache Software Foundation infoinitially developed by FacebookKineticaOracle infooriginally developed by Sleepycat, which was acquired by OracleThe Linux Foundation, PlanetScale
Initial release2012201219942013
Current release3.1.3, April 20227.1, August 202118.1.40, May 202015.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infocommercial license availableOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++C, Java, C++ (depending on the Berkeley DB edition)Go
Server operating systemsAll OS with a Java VMLinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Docker
Linux
macOS
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.noyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsyes infoSQL interfaced based on SQLite is availableyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
Thrift
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC++
Java
PHP
Python
C++
Java
JavaScript (Node.js)
Python
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsnoyes infoproprietary syntax
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoonly for the SQL APIyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyesyes
User concepts infoAccess controlAccess rights for users, groups and rolesAccess rights for users and roles on table levelnoUsers with fine-grained authorization concept infono user groups or roles

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More resources
HiveKineticaOracle Berkeley DBVitess
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