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DBMS > Kinetica vs. OmniSci

System Properties Comparison Kinetica vs. OmniSci

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Our visitors often compare Kinetica and OmniSci with Brytlyt, Vertica and MongoDB.

Editorial information provided by DB-Engines
NameKinetica  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 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
Score0.38
Rank#201  Overall
#98  Relational DBMS
Score2.42
Rank#93  Overall
#47  Relational DBMS
Websitewww.kinetica.comwww.omnisci.com
Technical documentationwww.kinetica.com/­docswww.omnisci.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 only 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
KineticaOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018
Recent citations in the news

Explore Why GPU Database Market Is Thriving Worldwide : Kinetica, OmniSci, SQream, Neo4j, NVIDIA, Brytlyt, Blazegraph, BlazingDB - Press Release
14 December 2018, Digital Journal

MarketsandMarkets forecasts the global GPU database market size to grow from USD 178 million in 2018 to USD 455 million by 2023, at a Compound Annual Growth Rate (CAGR) of 20.7% during 2018-2023
12 December 2018, PRNewswire

GPU Database Market Worth $455 Million by 2023 - Exclusive Report by MarketsandMarkets™
5 December 2018, PRNewswire

Leveraging the Cloud to Better Mine Data in the Extreme Data Economy
10 December 2018, insideBIGDATA

Analyst Predict: GPU Database Market Size to Grow at CAGR of +20% by 2023 – Know About Growth with Technology, Analysis by Regions, Type, Application and Top Key Players - Press Release
11 December 2018, Digital Journal

provided by Google News

Explore Why GPU Database Market Is Thriving Worldwide : Kinetica, OmniSci, SQream, Neo4j, NVIDIA, Brytlyt, Blazegraph, BlazingDB - Press Release
14 December 2018, Digital Journal

MarketsandMarkets forecasts the global GPU database market size to grow from USD 178 million in 2018 to USD 455 million by 2023, at a Compound Annual Growth Rate (CAGR) of 20.7% during 2018-2023
12 December 2018, PRNewswire

GPU Database Market Worth $455 Million by 2023 - Exclusive Report by MarketsandMarkets™
5 December 2018, PRNewswire

Analyst Predict: GPU Database Market Size to Grow at CAGR of +20% by 2023 – Know About Growth with Technology, Analysis by Regions, Type, Application and Top Key Players - Press Release
11 December 2018, Digital Journal

GPU Database Market boosting the growth Worldwide: Market dynamics and trends, efficiencies Forecast 2025 | Kinetica, OmniSci, SQream, Neo4j, NVIDIA, Brytlyt, Blazegraph, BlazingDB
6 December 2018, openPR

provided by Google News

Job opportunities

Senior Solutions Engineer (East Coast)
Kinetica DB, New York, NY

Senior Solutions Engineer (West Coast)
Kinetica DB, San Francisco, CA

Community Developer Advocate - INTERN
OmniSci, San Francisco, CA

Community Developer Advocate
OmniSci, Remote

Sales Director - Department of Defense
OmniSci, Washington, DC

Engineering Manager - Backend Core Team
OmniSci, San Francisco, CA

Senior Manager - Technical Marketing
OmniSci, San Francisco, CA

jobs by Indeed




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