DB-EnginesInfluxDB download bannerEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Kinetica vs. OmniSci vs. RavenDB

System Properties Comparison Kinetica vs. OmniSci vs. RavenDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018  Xexclude from comparisonRavenDB  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 GPUsOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMSRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.53
Rank#199  Overall
#97  Relational DBMS
Score2.08
Rank#105  Overall
#52  Relational DBMS
Score3.86
Rank#71  Overall
#12  Document stores
Websitewww.kinetica.comwww.omnisci.comravendb.net
Technical documentationwww.kinetica.com/­docswww.omnisci.com/­docs/­latestravendb.net/­docs
DeveloperKineticaMapD Technologies, Inc.Hibernating Rhinos
Initial release201220162010
Current release6.0V44.2, May 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
RavenDB Cloud: Deploy a multi-node managed cluster in minutes. 10% discount for all users throughout 2019.
Implementation languageC, C++C++ and CUDAC#
Server operating systemsLinuxLinuxLinux
macOS
Raspberry Pi
Windows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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 indexesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like query language (RQL)
APIs and other access methodsRESTful HTTP API
JDBC
ODBC
Thrift
JDBC
ODBC
.NET Client API
Java Client API
Python Client API
RESTful HTTP API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/Thrift
Python
.Net
C#
Go
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsnoyes
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-slave replicationMaster-master replicationMulti-master replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoMapReduce functions can be defined in Linq
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID, Cluster-wide transaction available
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 levelfine grained access rights according to SQL-standardAccess control on document level using the Authorization Bundle
More information provided by the system vendor
KineticaOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018RavenDB
Specific characteristicsRavenDB is the pioneer NoSQL Document Database that is fully transactional (ACID)...
» more
Competitive advantagesRavenDB is easy to setup and secure. You can do it in a matter of minutes . Easy...
» more
Typical application scenariosIoT for Edge Deployments Fraud Detection Recommendation Engines Product Catalogs...
» more
Key customersToyota, Capgemini, Vodafone, Medicaid, Asos, Nomura, RMS Automotive, MSNBC, Pluralsight,...
» more
Market metrics2 million+ downloads 1000+ customers including Fortune 500 large enterprises
» more
Licensing and pricing modelsRavenDB is available on-premise and in the cloud. RavenDB Cloud is available on AWS...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
KineticaOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018RavenDB
Recent citations in the news

The insideBIGDATA IMPACT 50 List for Q4 2019
15 October 2019, insideBIGDATA

GPU Database Market Is Touching New Level|Kinetica, Omnisci, Sqream
11 October 2019, Global Industry Network

GPU Database Market 2019 Precise Outlook – Anaconda, NVIDIA, Brytlyt, Neo4j, Blazegraph, Kinetica, Fuzzy Logix
17 October 2019, marketresearchjournals

Applying Active Analytics To Dynamic Replenishment
10 October 2019, Forbes

Moving from passive to active analytics for data innovation: the use cases
15 October 2019, Information Age

provided by Google News

GPU Database Market Is Touching New Level|Kinetica, Omnisci, Sqream
11 October 2019, Global Industry Network

GPU Database Market 2019 Precise Outlook – Anaconda, NVIDIA, Brytlyt, Neo4j, Blazegraph, Kinetica, Fuzzy Logix
17 October 2019, marketresearchjournals

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

Emerging Growth on GPU Database Market 2019-2026: Leading Companies like Kinetica, Omnisci, Sqream, Neo4j, Nvidia, Brytlyt, Jedox, Blazegraph, Blazingdb, Zilliz, Heterodb, H2o.Ai
26 September 2019, Market Research Scoop

Huge Demands for New Opportunities on Graphics Processing Unit Database Market 2028 Forecasts and Analysis with Top Key Players like – Zilliz, Brytlyt, Jedox AG, OmniSci
7 October 2019, Sound On Sound Fest

provided by Google News

Key considerations for CIOs while selecting DB infrastructure solutions
27 September 2019, InfotechLead.com

Review: NoSQL database RavenDB
20 March 2019, TechGenix

RavenDB Cloud automates database management
3 July 2019, TechTarget

RavenDB Adds Graph Queries
15 May 2019, Datanami

RavenDB vs MongoDB Database for Modern Apps
28 August 2019, Communal News

provided by Google News

Job opportunities

Machine Learning Engineer
BAIN & COMPANY, Los Angeles, CA

Sr. Software Engineer (Computer Vision/Data Visualization)
Kinetica DB, Arlington, VA

Application Support Engineer (Eastern US)
OmniSci, Remote

Senior Database Engineer
OmniSci, San Francisco, CA

Senior Compiler Engineer
OmniSci, San Francisco, CA

Senior Backend Test Engineer
OmniSci, San Francisco, CA

Sales Director - Department of Defense
OmniSci, Washington, DC

GC JUNIOR DEVELOPER
The Home Depot, Houston, TX

Data Scientists
Inductive Minds, Washington, DC

Developer on Test II
Performant Financial Corporation, San Francisco, CA

Sitecore Developer
XCentium, United States

Full Stack Developer
David Weekley Homes, Houston, TX

jobs by Indeed




Share this page

Featured Products

RavenDB logo

Setup a fully managed RavenDB Cloud Database in minutes. Enjoy hosting, management, backups all in one place.
Grab a Free Instance

Couchbase logo

SQL + JSON + NoSQL.
Power, flexibility & scale.
All open source.
Get started now.

Redis logo

Hosted, serverless DBaaS
in 3 steps.

30MB Free!
Start now.

Neo4j logo

Get your free copy of the new O'Reilly book Graph Algorithms with 20+ examples for
machine learning, graph analytics and more.

Present your product here