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DBMS > Hive vs. Kdb vs. Microsoft Azure Table Storage vs. Sequoiadb vs. Spark SQL

System Properties Comparison Hive vs. Kdb vs. Microsoft Azure Table Storage vs. Sequoiadb vs. Spark SQL

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonKdb  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSequoiadb  Xexclude from comparisonSpark SQL  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopHigh performance Time Series DBMSA Wide Column Store for rapid development using massive semi-structured datasetsNewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMS
Vector DBMS
Wide column storeDocument store
Relational DBMS
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitehive.apache.orgkx.comazure.microsoft.com/­en-us/­services/­storage/­tableswww.sequoiadb.comspark.apache.org/­sql
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homecode.kx.comwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoinitially developed by FacebookKx Systems, a division of First Derivatives plcMicrosoftSequoiadb Ltd.Apache Software Foundation
Initial release20122000 infokdb was released 2000, kdb+ in 2003201220132014
Current release3.1.3, April 20223.6, May 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree 32-bit versioncommercialOpen Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaqC++Scala
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
hostedLinuxLinux
OS X
Windows
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes infooid, date, timestamp, binary, regexyes
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.yesnonono
Secondary indexesyesyes infotable attribute 'grouped'noyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (q)noSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Thrift
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
RESTful HTTP APIproprietary protocol using JSONJDBC
ODBC
Supported programming languagesC++
Java
PHP
Python
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsnoJavaScriptno
Triggersnoyes infowith viewsnonono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding infoImplicit feature of the cloud serviceShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno infosimilar paradigm used for internal processingnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingDocument is locked during a transactionno
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.yesnonono
User concepts infoAccess controlAccess rights for users, groups and rolesrights management via user accountsAccess rights based on private key authentication or shared access signaturessimple password-based access controlno
More information provided by the system vendor
HiveKdbMicrosoft Azure Table StorageSequoiadbSpark SQL
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
HiveKdbMicrosoft Azure Table StorageSequoiadbSpark SQL
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