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DBMS > JaguarDB vs. Kinetica vs. MongoDB

System Properties Comparison JaguarDB vs. Kinetica vs. MongoDB

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Editorial information provided by DB-Engines
NameJaguarDB  Xexclude from comparisonKinetica  Xexclude from comparisonMongoDB  Xexclude from comparison
DescriptionPerformant, highly scalable DBMS for AI and IoT applicationsFully vectorized database across both GPUs and CPUsOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelKey-value storeRelational DBMSDocument store
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#377  Overall
#59  Key-value stores
Score0.45
Rank#268  Overall
#124  Relational DBMS
Score469.33
Rank#5  Overall
#1  Document stores
Websitewww.datajaguar.comwww.kinetica.comwww.mongodb.com
Technical documentationwww.datajaguar.com/­support.phpwww.kinetica.com/­docsdocs.mongodb.com/­manual
DeveloperDataJaguar, Inc.KineticaMongoDB, Inc
Initial release201520122009
Current release2.9.4 September 20187.1, August 20216.0.1, August 2022
License infoCommercial or Open SourceOpen Source infoGPL V3.0commercialOpen Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.
Cloud-based only infoOnly available as a cloud servicenonono infoMongoDB available as DBaaS (MongoDB Atlas)
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
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Implementation languageC++ infothe server part. Clients available in other languagesC, C++C++
Server operating systemsLinuxLinuxLinux
OS X
Solaris
Windows
Data schemeyesyesschema-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.
Typing infopredefined data types such as float or dateyesyesyes infostring, integer, double, decimal, boolean, date, object_id, geospatial
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 indexesyesyesyes
SQL infoSupport of SQLA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersSQL-like DML and DDL statementsRead-only SQL queries via the MongoDB Connector for BI
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
proprietary protocol using JSON
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Actionscript 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
Server-side scripts infoStored proceduresnouser defined functionsJavaScript
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoin MongoDB Atlas only
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynoyesno infotypically not used, however similar functionality with DBRef possible
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoMulti-document ACID Transactions with snapshot isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infooptional, enabled by default
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMyes infoIn-memory storage engine introduced with MongoDB version 3.2
User concepts infoAccess controlrights management via user accountsAccess rights for users and roles on table levelAccess rights for users and roles
More information provided by the system vendor
JaguarDBKineticaMongoDB
Specific characteristicsNative and fully vectorized database across both GPUs and CPUs, with memory first...
» more
Competitive advantagesBest in class geospatial and temporal analytics. Lockless architecture provides real-time...
» more
Typical application scenariosAny application requiring (1) real time insights, (2) time series analysis (3) geospatial...
» more
Key customersCitibank, US Air Force, Softbank, OVO, Telkomsel, USPS, 2 of the top 3 US Telcos,...
» more
Market metricsThe largest IoT deployment in the world, NORAD, runs on Kinetica.
» more
Licensing and pricing modelsAlways Free Tier in the Cloud, Pay-As-You-Go Consumption Based Pricing, and Portable...
» more

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More resources
JaguarDBKineticaMongoDB
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