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DBMS > Kinetica vs. MapD

System Properties Comparison Kinetica vs. MapD

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Our visitors often compare Kinetica and MapD with Brytlyt, Vertica and Microsoft SQL Server.

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMapD  Xexclude from comparison
DescriptionGPU-accelerated database for real-time analysis of large and streaming datasetsA high performance, in-memory, column-oriented RDBMS, designed to run on GPUs
Primary database modelRelational DBMSRelational DBMS
Secondary database modelsKey-value storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#192  Overall
#95  Relational DBMS
Score2.38
Rank#89  Overall
#43  Relational DBMS
Websitewww.kinetica.comwww.mapd.com
Technical documentationwww.kinetica.com/­docswww.mapd.com/­docs/­latest
DeveloperKineticaMapD Technologies, Inc.
Initial release20122016
Current release6.0V4
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition available
Cloud-based infoOnly available as a cloud servicenono
Implementation languageC, C++C++ and CUDA
Server operating systemsLinuxLinux
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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 indexesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP API
JDBC
ODBC
Thrift
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresuser defined functionsno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-slave replicationMaster-master replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
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 levelfine grained access rights according to SQL-standard

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More resources
KineticaMapD
Recent citations in the news

Kinetica to Discuss GPU-powered Analytics for the Extreme Data Economy at Strata Data Conference in New York City
6 September 2018, Business Wire (press release)

Kinetica Maps Future of Automotive Industry Powered by Extreme Data
29 August 2018, Business Wire (press release)

Enough Training, Let's Get Down To The AI Supermarket
18 September 2018, Forbes

Kinetica Becomes a Member of The Linux Foundation to Enable Advanced Analytics for Automotive
30 August 2018, Read IT Quik

Google Hands Off Kubernetes to the Cloud Native Computing Foundation, Kinetica Joins Automotive Grade Linux ...
30 August 2018, Linux Journal

provided by Google News

MapD's GPU-Powered Database Now Available in Google Cloud's Marketplace
19 July 2018, Datanami

MapD Fires Up GPU Cloud Service
5 April 2018, The Next Platform

O'Reilly and Cloudera Announce Inaugural Strata Data Awards Finalists
4 September 2018, Business Wire (press release)

Alibaba Group leads $26.4M Series B in GPU database provider SQream
30 May 2018, TechCrunch

GPU databases are coming of age
26 March 2018, ZDNet

provided by Google News

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