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DBMS > Kinetica vs. Microsoft Azure SQL Database vs. Spark SQL vs. Warp 10 vs. XTDB

System Properties Comparison Kinetica vs. Microsoft Azure SQL Database vs. Spark SQL vs. Warp 10 vs. XTDB

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSpark SQL  Xexclude from comparisonWarp 10  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL ServerSpark SQL is a component on top of 'Spark Core' for structured data processingTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBaseA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMSDocument store
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
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websitewww.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasespark.apache.org/­sqlwww.warp10.iogithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sqlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.warp10.io/­content/­02_Getting_startedwww.xtdb.com/­docs
DeveloperKineticaMicrosoftApache Software FoundationSenXJuxt Ltd.
Initial release20122010201420152019
Current release7.1, August 2021V123.5.0 ( 2.13), September 20231.19, September 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache License 2.0Open Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++ScalaJavaClojure
Server operating systemsLinuxhostedLinux
OS X
Windows
Linux
OS X
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeyesyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyesyes, extensible-data-notation format
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.noyesnonono
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like DML and DDL statementsnolimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
HTTP API
Jupyter
WebSocket
HTTP REST
JDBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Clojure
Java
Server-side scripts infoStored proceduresuser defined functionsTransact SQLnoyes infoWarpScriptno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding infobased on HBasenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, with always 3 replicas availablenoneselectable replication factor infobased on HBaseyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integrityyesyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlAccess rights for users and roles on table levelfine grained access rights according to SQL-standardnoMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
KineticaMicrosoft Azure SQL Database infoformerly SQL AzureSpark SQLWarp 10XTDB infoformerly named Crux
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