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DBMS > Kinetica vs. Snowflake vs. Spark SQL vs. SQream DB vs. Warp 10

System Properties Comparison Kinetica vs. Snowflake vs. Spark SQL vs. SQream DB vs. Warp 10

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSnowflake  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQream DB  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsCloud-based data warehousing service for structured and semi-structured dataSpark SQL is a component on top of 'Spark Core' for structured data processinga GPU-based, columnar RDBMS for big data analytics workloadsTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score121.33
Rank#9  Overall
#6  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitewww.kinetica.comwww.snowflake.comspark.apache.org/­sqlsqream.comwww.warp10.io
Technical documentationdocs.kinetica.comdocs.snowflake.net/­manuals/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.comwww.warp10.io/­content/­02_Getting_started
DeveloperKineticaSnowflake Computing Inc.Apache Software FoundationSQream TechnologiesSenX
Initial release20122014201420172015
Current release7.1, August 20213.5.0 ( 2.13), September 20232022.1.6, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercialOpen Source infoApache License 2.0
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++ScalaC++, CUDA, Haskell, Java, ScalaJava
Server operating systemsLinuxhostedLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeyesyes infosupport of semi-structured data formats (JSON, XML, Avro)yesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, ANSI Standard SQL Typesyes
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 indexesyesnonono
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like DML and DDL statementsyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
CLI Client
JDBC
ODBC
JDBC
ODBC
.Net
JDBC
ODBC
HTTP API
Jupyter
WebSocket
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
JavaScript (Node.js)
Python
Java
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsnouser defined functions in Pythonyes infoWarpScript
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeno infosimilar concept for controling cloud resourcesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingyesyes, utilizing Spark Corehorizontal and vertical partitioningSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnonenoneselectable replication factor infobased on HBase
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 ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integrityyesyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDno
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.yes infoGPU vRAM or System RAMnonoyes
User concepts infoAccess controlAccess rights for users and roles on table levelUsers with fine-grained authorization concept, user roles and pluggable authenticationnoMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
KineticaSnowflakeSpark SQLSQream DBWarp 10
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