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DBMS > Cassandra vs. Kinetica vs. Microsoft Azure Data Explorer vs. OmniSci

System Properties Comparison Cassandra vs. Kinetica vs. Microsoft Azure Data Explorer vs. OmniSci

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Editorial information provided by DB-Engines
NameCassandra  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018  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 datasetsFully managed big data interactive analytics platformA high performance, in-memory, column-oriented RDBMS, designed to run on GPUs
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
Score1.51
Rank#120  Overall
#62  Relational DBMS
Score1.80
Rank#109  Overall
#54  Relational DBMS
Websitecassandra.apache.orgwww.kinetica.comazure.microsoft.com/­services/­data-explorerwww.omnisci.com
Technical documentationcassandra.apache.org/­doc/­latestwww.kinetica.com/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.omnisci.com/­docs/­latest
DeveloperApache Software Foundation infoApache top level project, originally developped by FacebookKineticaMicrosoftMapD Technologies, Inc.
Initial release2008201220192016
Current release3.11.4, February 20196.0V4
License infoCommercial or Open SourceOpen Source infoApache version 2commercialcommercialOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++C++ and CUDA
Server operating systemsBSD
Linux
OS X
Windows
LinuxhostedLinux
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.nonoyesno
Secondary indexesrestricted infoonly equality queries, not always the best performing solutionyesno
SQL infoSupport of SQLSQL-like SELECT, DML and DDL statements (CQL)SQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsProprietary protocol infoCQL (Cassandra Query Language, an SQL-like language)
Thrift
RESTful HTTP API
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Thrift
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
.Net
Java
JavaScript (Node.js)
PowerShell
Python
R
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresnouser defined functionsYes. Languages: KQL, Python, Rno
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangeTable-level update policy rules can be used to automatically run a query and ingest its results when data is ingested into another table.no
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"ShardingSharding infoImplicit feature of the cloud serviceSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infoRepresentation of geographical distribution of servers is possibleMaster-slave replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Master-master replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
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 configurationEventual Consistency
Immediate Consistency
Immediate 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 RAMnoyes
User concepts infoAccess controlAccess rights for users can be defined per objectAccess rights for users and roles on table levelAzure Active Directory Authenticationfine grained access rights according to SQL-standard
More information provided by the system vendor
CassandraKineticaMicrosoft Azure Data ExplorerOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018
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...
» more
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
CassandraKineticaMicrosoft Azure Data ExplorerOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018
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