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DBMS > Blueflood vs. Kinetica vs. openGauss vs. Spark SQL

System Properties Comparison Blueflood vs. Kinetica vs. openGauss vs. Spark SQL

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Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonKinetica  Xexclude from comparisonopenGauss  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on CassandraFully vectorized database across both GPUs and CPUsAn enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by HuaweiSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
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
Score1.06
Rank#184  Overall
#84  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteblueflood.iowww.kinetica.comgitee.com/­opengauss
opengauss.org
spark.apache.org/­sql
Technical documentationgithub.com/­rax-maas/­blueflood/­wikidocs.kinetica.comdocs.opengauss.org/­en
gitee.com/­opengauss/­docs
spark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperRackspaceKineticaHuawei and openGauss communityApache Software Foundation
Initial release2013201220192014
Current release7.1, August 20213.0, March 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++C, C++, JavaScala
Server operating systemsLinux
OS X
LinuxLinuxLinux
OS X
Windows
Data schemepredefined schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononono
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsANSI SQL 2011SQL-like DML and DDL statements
APIs and other access methodsHTTP RESTJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
C++
Java
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsyesno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardinghorizontal partitioning (by range, list and hash)yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraSource-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
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 configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMnono
User concepts infoAccess controlnoAccess rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standardno

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BluefloodKineticaopenGaussSpark SQL
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