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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, Microsoft SQL Server and Vertica.

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
Score0.32
Rank#189  Overall
#92  Relational DBMS
Score2.10
Rank#90  Overall
#44  Relational DBMS
Websitewww.kinetica.comwww.mapd.com
Technical documentationwww.kinetica.com/­docswww.mapd.com/­docs/­latest
DeveloperKineticaMapD Technologies, Inc.
Initial release20122016
Current release6.0V3
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
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 levelDB level access control for users

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More resources
KineticaMapD
Recent citations in the news

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

Kinetica Names Michael Mahoney as Worldwide Vice President of Solution Engineering
19 June 2018, Business Wire (press release)

Dell EMC & Kinetica sign OEM agreement for the 'extreme data economy'
14 June 2018, ChannelLife NZ

Creating the new data-powered bank
20 June 2018, Bankless Times

Nvidia Riding High as GPU Workloads and Capabilities Soar
27 March 2018, Datanami

provided by Google News

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

ZILLIZ Speeds up GPU Database Commercialization Layout After Completing $10 Million A1 Round Financing
6 June 2018, PR Newswire (press release)

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

MapD Rolls GPU Cloud
3 April 2018, Datanami

Big Data Market: 2018-2030: Big Data Vendors will Pocket Over $65 Billion from Hardware, Software and Professional ...
22 June 2018, PR Newswire (press release)

provided by Google News

Job opportunities

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Kinetica DB, Philadelphia, PA

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