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DBMS > Blueflood vs. Kinetica vs. Rockset vs. Spark SQL vs. Splice Machine

System Properties Comparison Blueflood vs. Kinetica vs. Rockset vs. Spark SQL vs. Splice Machine

Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonKinetica  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on CassandraFully vectorized database across both GPUs and CPUsA scalable, reliable search and analytics service in the cloud, built on RocksDBSpark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSRelational DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#346  Overall
#33  Time Series DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.82
Rank#212  Overall
#36  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteblueflood.iowww.kinetica.comrockset.comspark.apache.org/­sqlsplicemachine.com
Technical documentationgithub.com/­rax-maas/­blueflood/­wikidocs.kinetica.comdocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-works
DeveloperRackspaceKineticaRocksetApache Software FoundationSplice Machine
Initial release20132012201920142014
Current release7.1, August 20213.5.0 ( 2.13), September 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++C++ScalaJava
Server operating systemsLinux
OS X
LinuxhostedLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemepredefined schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesdynamic typingyesyes
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.nonono infoingestion from XML files supportedno
Secondary indexesnoyesall fields are automatically indexednoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsRead-only SQL queries, including JOINsSQL-like DML and DDL statementsyes
APIs and other access methodsHTTP RESTJDBC
ODBC
RESTful HTTP API
HTTP RESTJDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsnonoyes infoJava
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangenonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingAutomatic shardingyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraSource-replica replicationyesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
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.noyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlnoAccess rights for users and roles on table levelAccess rights for users and organizations can be defined via Rockset consolenoAccess rights for users, groups and roles according to SQL-standard

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More resources
BluefloodKineticaRocksetSpark SQLSplice Machine
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