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DBMS > Kinetica vs. Microsoft Azure Cosmos DB vs. OmniSci

System Properties Comparison Kinetica vs. Microsoft Azure Cosmos DB vs. OmniSci

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018  Xexclude from comparison
DescriptionGPU-accelerated database for real-time analysis of large and streaming datasetsGlobally distributed, horizontally scalable, multi-model database serviceA high performance, in-memory, column-oriented RDBMS, designed to run on GPUs
Primary database modelRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.60
Rank#192  Overall
#95  Relational DBMS
Score26.28
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#4  Key-value stores
#3  Wide column stores
Score2.57
Rank#96  Overall
#48  Relational DBMS
Websitewww.kinetica.comazure.microsoft.com/­services/­cosmos-dbwww.omnisci.com
Technical documentationwww.kinetica.com/­docsdocs.microsoft.com/­en-us/­azure/­cosmos-dbwww.omnisci.com/­docs/­latest
DeveloperKineticaMicrosoftMapD Technologies, Inc.
Initial release201220142016
Current release6.0V4
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++ and CUDA
Server operating systemsLinuxhostedLinux
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoJSON typesyes
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.nono
Secondary indexesyesyes infoAll properties auto-indexed by defaultno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageyes
APIs and other access methodsRESTful HTTP API
JDBC
ODBC
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Thrift
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresuser defined functionsJavaScriptno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeJavaScriptno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-slave replicationyes infoImplicit feature of the cloud serviceMaster-master replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationBounded Staleness
Consistent Prefix
Session Consistency
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Immediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoMulti-item ACID transactions with snapshot isolation within a partitionno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users and roles on table levelAccess rights can be defined down to the item levelfine grained access rights according to SQL-standard
More information provided by the system vendor
KineticaMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018
Specific characteristicsAzure Cosmos DB is Microsoft™s globally-distributed, horizontally scalable, multi-model...
» more
Competitive advantagesGlobal distribution Easily build globally-distributed applications without the hassle...
» more
Typical application scenariosAzure Cosmos DB enables writing globally distributed applications and allows you...
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Key customersJet.com, Asos, Real Madrid, Orange Tribes, MSN, Telenor, NextGames, Schneider Electric,...
» more
Market metricsGartner Research positions Microsoft as the leader in the Magic Quadrant Operational...
» more
Licensing and pricing modelsWith Azure Cosmos DB, pay only for the storage you use and the throughput you provision...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
KineticaMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018
Recent citations in the news

Review: OmniSci GPU database lifts huge data sets
1 April 2019, InfoWorld

Field Report: GPU Technology Conference 2019 #GTC19
4 April 2019, insideBIGDATA

GPU Database Market to Witness Robust Expansion by 2025 | Kinetica, OmniSci, SQream, Neo4j, NVIDIA, Brytlyt, Blazegraph, BlazingDB
28 March 2019, Market Reports

Kinetica Could Boost Nvidia In $70B Big Data Market
12 October 2018, Forbes

Kinetica Delivers GPU-Accelerated Analytics Engine to SoftBank
1 November 2018, Business Wire

provided by Google News

Here's how Skype manages the data of 4 billion users leveraging Azure Cosmos DB
17 April 2019, OnMSFT

Microsoft says its Cosmos DB provides planet-scale, low-effort NoSQL data access
8 April 2019, iTWire

Microsoft: The sky's the limit for your data with Cosmos DB
8 April 2019, IT Brief New Zealand

AnzoGraph review: A graph database for deep analytics
15 April 2019, InfoWorld

Azure Cosmos DB gets cheaper, Azure Machine Learning gets smarter
4 December 2018, ZDNet

provided by Google News

Review: OmniSci GPU database lifts huge data sets
1 April 2019, InfoWorld

New Data Science Platforms Highlight Nvidia's GPU Conference
25 March 2019, eWeek

GPU Database Market to Witness Robust Expansion by 2025 | Kinetica, OmniSci, SQream, Neo4j, NVIDIA, Brytlyt, Blazegraph, BlazingDB
28 March 2019, Market Reports

Graphics Processing Unit Database Market Growing Demand and Trends 2019 to 2028
11 April 2019, The Smart CMS

OmniSci, formerly MapD, gets $55 million in series C funding
4 October 2018, Packt Hub

provided by Google News

Job opportunities

Sr. Solutions Engineer (West Coast)
Kinetica DB, Seattle, WA

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