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DBMS > Blueflood vs. Hazelcast vs. Kinetica vs. Rockset vs. Spark SQL

System Properties Comparison Blueflood vs. Hazelcast vs. Kinetica vs. Rockset vs. Spark SQL

Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonHazelcast  Xexclude from comparisonKinetica  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on CassandraA widely adopted in-memory data gridFully 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 DBMSKey-value storeRelational DBMSDocument storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial 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
Score5.46
Rank#61  Overall
#7  Key-value stores
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.iohazelcast.comwww.kinetica.comrockset.comspark.apache.org/­sql
Technical documentationgithub.com/­rax-maas/­blueflood/­wikihazelcast.org/­imdg/­docsdocs.kinetica.comdocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperRackspaceHazelcastKineticaRocksetApache Software Foundation
Initial release20132008201220192014
Current release5.3.6, November 20237.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses 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 languageJavaJavaC, C++C++Scala
Server operating systemsLinux
OS X
All OS with a Java VMLinuxhostedLinux
OS X
Windows
Data schemepredefined schemeschema-freeyesschema-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.noyes infothe object must implement a serialization strategynono infoingestion from XML files supportedno
Secondary indexesnoyesyesall fields are automatically indexedno
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statementsRead-only SQL queries, including JOINsSQL-like DML and DDL statements
APIs and other access methodsHTTP RESTJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
HTTP RESTJDBC
ODBC
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor Servicesuser defined functionsnono
Triggersnoyes infoEventsyes 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 Cassandrayes infoReplicated MapSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitednonono
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.noyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlnoRole-based access controlAccess 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
BluefloodHazelcastKineticaRocksetSpark SQL
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