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DBMS > Blueflood vs. IBM Db2 Event Store vs. Kinetica vs. Rockset vs. Spark SQL

System Properties Comparison Blueflood vs. IBM Db2 Event Store vs. Kinetica vs. Rockset vs. Spark SQL

Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonKinetica  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on CassandraDistributed Event Store optimized for Internet of Things use casesFully 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 processing
Primary database modelTime Series DBMSEvent Store
Time Series DBMS
Relational DBMSDocument storeRelational 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
Score0.27
Rank#309  Overall
#2  Event Stores
#28  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
Websiteblueflood.iowww.ibm.com/­products/­db2-event-storewww.kinetica.comrockset.comspark.apache.org/­sql
Technical documentationgithub.com/­rax-maas/­blueflood/­wikiwww.ibm.com/­docs/­en/­db2-event-storedocs.kinetica.comdocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperRackspaceIBMKineticaRocksetApache Software Foundation
Initial release20132017201220192014
Current release2.07.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infofree developer edition availablecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C, C++C++Scala
Server operating systemsLinux
OS X
Linux infoLinux, macOS, Windows for the developer additionLinuxhostedLinux
OS X
Windows
Data schemepredefined schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesdynamic typingyes
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 infoingestion from XML files supportedno
Secondary indexesnonoyesall fields are automatically indexedno
SQL infoSupport of SQLnoyes infothrough the embedded Spark runtimeSQL-like DML and DDL statementsRead-only SQL queries, including JOINsSQL-like DML and DDL statements
APIs and other access methodsHTTP RESTADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
HTTP RESTJDBC
ODBC
Supported programming languagesC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C++
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesuser defined functionsnono
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingShardingAutomatic shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraActive-active shard replicationSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononono
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users and roles on table levelAccess rights for users and organizations can be defined via Rockset consoleno

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More resources
BluefloodIBM Db2 Event StoreKineticaRocksetSpark SQL
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