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DBMS > Cassandra vs. Kinetica vs. OmniSci vs. Spark SQL

System Properties Comparison Cassandra vs. Kinetica vs. OmniSci vs. Spark SQL

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Editorial information provided by DB-Engines
NameCassandra  Xexclude from comparisonKinetica  Xexclude from comparisonOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionWide-column store based on ideas of BigTable and DynamoDB infoOptimized for write accessGPU-accelerated database for real-time analysis of large and streaming datasetsA high performance, in-memory, column-oriented RDBMS, designed to run on GPUsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelWide column storeRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score123.40
Rank#10  Overall
#1  Wide column stores
Score0.54
Rank#194  Overall
#96  Relational DBMS
Score1.80
Rank#109  Overall
#54  Relational DBMS
Score16.15
Rank#35  Overall
#21  Relational DBMS
Websitecassandra.apache.orgwww.kinetica.comwww.omnisci.comspark.apache.org/­sql
Technical documentationcassandra.apache.org/­doc/­latestwww.kinetica.com/­docswww.omnisci.com/­docs/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top level project, originally developped by FacebookKineticaMapD Technologies, Inc.Apache Software Foundation
Initial release2008201220162014
Current release3.11.4, February 20196.0V4v2.4.4, September 2019
License infoCommercial or Open SourceOpen Source infoApache version 2commercialOpen Source infoApache Version 2; enterprise edition availableOpen 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++ and CUDAScala
Server operating systemsBSD
Linux
OS X
Windows
LinuxLinuxLinux
OS X
Windows
Data schemeschema-freeyesyesyes
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 indexesrestricted infoonly equality queries, not always the best performing solutionyesnono
SQL infoSupport of SQLSQL-like SELECT, DML and DDL statements (CQL)SQL-like DML and DDL statementsyesSQL-like DML and DDL statements
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language, an SQL-like language)
Thrift
RESTful HTTP API
JDBC
ODBC
Thrift
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript infoNode.js
Perl
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/Thrift
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsnono
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"ShardingSharding infoRound robinyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infoRepresentation of geographical distribution of servers is possibleMaster-slave replicationMaster-master replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoAtomicity and isolation are supported for single operationsnonono
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 RAMyesno
User concepts infoAccess controlAccess rights for users can be defined per objectAccess rights for users and roles on table levelfine grained access rights according to SQL-standardno
More information provided by the system vendor
CassandraKineticaOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018Spark SQL
Specific characteristicsApache Cassandra is the leading NoSQL, distributed database management system, well...
» more
Competitive advantagesNo single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenariosInternet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customersApple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metricsCassandra is used by 40% of the Fortune 100.
» more
Licensing and pricing modelsApache license  Pricing for commercial distributions provided by DataStax and available...
» more

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More resources
CassandraKineticaOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018Spark SQL
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Conferences and events

Spark Summit Europe 2019
Amsterdam, Netherlands, 15-17 October 2019

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