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

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

Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonKinetica  Xexclude from comparisonNCache  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on CassandraFully vectorized database across both GPUs and CPUsOpen-Source and Enterprise in-memory Key-Value StoreA 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 DBMSRelational DBMSKey-value storeDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Search engine infoUsing distributed Lucene
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
Score0.96
Rank#195  Overall
#29  Key-value stores
Score0.82
Rank#212  Overall
#36  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteblueflood.iowww.kinetica.comwww.alachisoft.com/­ncacherockset.comspark.apache.org/­sql
Technical documentationgithub.com/­rax-maas/­blueflood/­wikidocs.kinetica.comwww.alachisoft.com/­resources/­docsdocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperRackspaceKineticaAlachisoftRocksetApache Software Foundation
Initial release20132012200520192014
Current release7.1, August 20215.3.3, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoEnterprise Edition availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++C#, .NET, .NET Core, JavaC++Scala
Server operating systemsLinux
OS X
LinuxLinux
Windows
hostedLinux
OS X
Windows
Data schemepredefined schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyespartial infoSupported data types are Lists, Queues, Hashsets, Dictionary and Counterdynamic 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 indexesnoyesyesall fields are automatically indexedno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.Read-only SQL queries, including JOINsSQL-like DML and DDL statements
APIs and other access methodsHTTP RESTJDBC
ODBC
RESTful HTTP API
IDistributedCache
JCache
LINQ
Proprietary native API
HTTP RESTJDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsno infosupport for stored procedures with SQL-Server CLRnono
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoNotificationsnono
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingyesAutomatic shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraSource-replica replicationyes, with selectable consistency levelyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
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 Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology
Eventual Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic locking and pessimistic lockingnono
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.noyes infoGPU vRAM or System RAMyesno
User concepts infoAccess controlnoAccess rights for users and roles on table levelAuthentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)Access rights for users and organizations can be defined via Rockset consoleno
More information provided by the system vendor
BluefloodKineticaNCacheRocksetSpark SQL
Specific characteristicsNCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more
Competitive advantagesNCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more
Typical application scenariosNCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more
Key customersBank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more
Market metricsMarket Leader in .NET Distributed Caching since 2005.
» more
Licensing and pricing modelsNCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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More resources
BluefloodKineticaNCacheRocksetSpark SQL
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