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DBMS > MongoDB vs. OmniSci vs. SQream DB

System Properties Comparison MongoDB vs. OmniSci vs. SQream DB

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Editorial information provided by DB-Engines
NameMongoDB  Xexclude from comparisonOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018  Xexclude from comparisonSQream DB  Xexclude from comparison
DescriptionOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureA high performance, in-memory, column-oriented RDBMS, designed to run on GPUsa GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelDocument storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Search engine infointegrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS infoTime Series Collections introduced in Release 5.0
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score493.55
Rank#5  Overall
#1  Document stores
Score1.23
Rank#157  Overall
#76  Relational DBMS
Score0.66
Rank#215  Overall
#107  Relational DBMS
Websitewww.mongodb.comwww.omnisci.comsqream.com
Technical documentationdocs.mongodb.com/­manualdocs.omnisci.comdocs.sqream.com
DeveloperMongoDB, IncMapD Technologies, Inc.SQream Technologies
Initial release200920162014
Current release5.0, July 20215.6, April 20212020.2, July 2020
License infoCommercial or Open SourceOpen Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.Open Source infoApache Version 2; enterprise edition availablecommercial
Cloud-based only infoOnly available as a cloud serviceno infoMongoDB available as DBaaS (MongoDB Atlas)nono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
  • MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.
  • ScaleGrid for MongoDB: Fully managed hosting for MongoDB database on AWS, Azure and DigitalOcean with high availability and SSH access on the #1 multi-cloud DBaaS.
Implementation languageC++C++ and CUDAC++, CUDA, Haskell
Server operating systemsLinux
OS X
Solaris
Windows
LinuxLinux
Data schemeschema-free infoAlthough schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.yesyes
Typing infopredefined data types such as float or dateyes infostring, integer, double, decimal, boolean, date, object_id, geospatialyesyes, ANSI Standard SQL Types
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.no
Secondary indexesyesnoyes
SQL infoSupport of SQLRead-only SQL queries via the MongoDB Connector for BIyesyes
APIs and other access methodsproprietary protocol using JSONJDBC
ODBC
Thrift
.Net
JDBC
ODBC
Supported programming languagesActionscript infounofficial driver
C
C#
C++
Clojure infounofficial driver
ColdFusion infounofficial driver
D infounofficial driver
Dart infounofficial driver
Delphi infounofficial driver
Erlang
Go
Groovy infounofficial driver
Haskell
Java
JavaScript
Lisp infounofficial driver
Lua infounofficial driver
MatLab infounofficial driver
Perl
PHP
PowerShell infounofficial driver
Prolog infounofficial driver
Python
R infounofficial driver
Ruby
Rust
Scala
Smalltalk infounofficial driver
Swift
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresJavaScriptnouser defined functions in Python
Triggersyes infoin MongoDB Atlas onlynono
Partitioning methods infoMethods for storing different data on different nodesSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.Sharding infoRound robinhorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
Multi-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataMulti-document ACID Transactions with snapshot isolationnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infooptional, enabled by defaultyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoIn-memory storage engine introduced with MongoDB version 3.2yes
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standard
More information provided by the system vendor
MongoDBOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018SQream DB
Specific characteristicsMongoDB’s application data platform provides developers a unified interface to power...
» more
Competitive advantagesThe MongoDB platform can be used by developers building transactional, operational,...
» more
Typical application scenariosInternet of Things and Time Series (Bosch, Jaguar Land Rover) Mobile (The Weather...
» more
Key customersADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
Market metrics175 million downloads, over 1.5M Atlas database clusters under management handling...
» more
Licensing and pricing modelsMongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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

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

More resources
MongoDBOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018SQream DB
DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2020
4 January 2021, Paul Andlinger, Matthias Gelbmann

PostgreSQL is the DBMS of the Year 2018
2 January 2019, Paul Andlinger, Matthias Gelbmann

PostgreSQL moves up one rank at the expense of MongoDB
1 September 2016, Paul Andlinger

show all

Conferences and events

MongoDB & Google Cloud Developer Summit
Virtual Event, 28 October 2021

MongoDB.Local London
London, 9 November 2021

Finished events

Introduction to MongoDB
Webinar, on demand, 27 July 2021 (finished)

Recent citations in the news

How MongoDB Beat Amazon
8 October 2021, The Motley Fool

How to Create Documents in MongoDB
13 October 2021, MakeUseOf

MongoDB Joins LOT Network To Protect Open Innovation For Developers
19 October 2021, PRNewswire

Why MongoDB Stock Is Falling Today
4 October 2021, Motley Fool

How Atlas Is Driving MongoDB's Growth
7 October 2021, Motley Fool

provided by Google News

GPU Database Market 2025: Strong Sales Outlook Ahead | Kinetica, OmniSci, SQream, Neo4j, NVIDIA, Brytlyt, Blazegraph, BlazingDB, Zilliz, and Jedox – Puck77
22 October 2021, Puck77

“Global GPU Database Market SWOT Analysis 2021 by Top Manufacturers: Kinetica , Omnisci , Sqream , Neo4j , Nvidia , Brytlyt , Jedox , Blazegraph , Blazingdb , Zilliz , Heterodb , H2o.Ai , Fastdata.Io , Fuzzy Logix , Graphistry , Anaconda , etc….” – Puck77
21 October 2021, Puck77

GPU Database Market 2021-2028: Major Trends and Key Developments | Kinetica, Omnisci, Sqream, Neo4j – Puck77
22 October 2021, Puck77

Unforeseen Drivers Contributing to GPU Database Market by Kinetica, OmniSci, SQream, Neo4j, NVIDIA – Puck77
20 October 2021, Puck77

GPU Database Market SWOT Analysis, Key Indicators, Forecast 2027 | Kinetica, OmniSci, SQream, Neo4j, NVIDIA, Brytlyt, Blazegraph, BlazingDB, Zilliz, and Jedox. – Puck77
21 October 2021, Puck77

provided by Google News

SQream Technologies raises $39.4 million for GPU-accelerated databases
24 June 2020, VentureBeat

Accelerated Databases In The Fast Lane
25 June 2020, The Next Platform

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

Stretching GPU Database Performance With Flash Arrays
26 February 2019, The Next Platform

SQream Delivers Enhanced Data Warehouse Solution
7 September 2018, Database Trends and Applications

provided by Google News

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