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DBMS > Hive vs. Kinetica vs. Microsoft SQL Server vs. PouchDB vs. SiteWhere

System Properties Comparison Hive vs. Kinetica vs. Microsoft SQL Server vs. PouchDB vs. SiteWhere

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonPouchDB  Xexclude from comparisonSiteWhere  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopFully vectorized database across both GPUs and CPUsMicrosofts flagship relational DBMSJavaScript DBMS with an API inspired by CouchDBM2M integration platform for persisting/querying time series data
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument storeTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Graph DBMS
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
Score821.56
Rank#3  Overall
#3  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websitehive.apache.orgwww.kinetica.comwww.microsoft.com/­en-us/­sql-serverpouchdb.comgithub.com/­sitewhere/­sitewhere
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.kinetica.comlearn.microsoft.com/­en-US/­sql/­sql-serverpouchdb.com/­guidessitewhere1.sitewhere.io/­index.html
DeveloperApache Software Foundation infoinitially developed by FacebookKineticaMicrosoftApache Software FoundationSiteWhere
Initial release20122012198920122010
Current release3.1.3, April 20227.1, August 2021SQL Server 2022, November 20227.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial inforestricted free version is availableOpen SourceOpen Source infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++C++JavaScriptJava
Server operating systemsAll OS with a Java VMLinuxLinux
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
Data schemeyesyesyesschema-freepredefined scheme
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.noyesnono
Secondary indexesyesyesyesyes infovia viewsno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsyesnono
APIs and other access methodsJDBC
ODBC
Thrift
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
HTTP REST infoonly for PouchDB Server
JavaScript API
HTTP REST
Supported programming languagesC++
Java
PHP
Python
C++
Java
JavaScript (Node.js)
Python
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
JavaScript
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsTransact SQL, .NET languages, R, Python and (with SQL Server 2019) JavaView functions in JavaScript
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingtables can be distributed across several files (horizontal partitioning); sharding through federationSharding infowith a proxy-based framework, named couchdb-loungeSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyes, but depending on the SQL-Server EditionMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyesyesno
User concepts infoAccess controlAccess rights for users, groups and rolesAccess rights for users and roles on table levelfine grained access rights according to SQL-standardnoUsers with fine-grained authorization concept

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More resources
HiveKineticaMicrosoft SQL ServerPouchDBSiteWhere
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