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DBMS > BaseX vs. MongoDB vs. Vertica

System Properties Comparison BaseX vs. MongoDB vs. Vertica

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Editorial information provided by DB-Engines
NameBaseX  Xexclude from comparisonMongoDB  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureColumnar relational DBMS designed to handle modern analytic workloads, enabling fast query performance
Primary database modelNative XML DBMSDocument storeRelational DBMS
Secondary database modelsSearch engine infointegrated Lucene index, currently in MongoDB Atlas only.Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.24
Rank#136  Overall
#4  Native XML DBMS
Score426.97
Rank#5  Overall
#1  Document stores
Score22.65
Rank#29  Overall
#17  Relational DBMS
Websitebasex.orgwww.mongodb.comwww.vertica.com
Technical documentationdocs.basex.orgdocs.mongodb.com/­manualwww.vertica.com/­documentation/­vertica
DeveloperBaseX GmbHMongoDB, IncVertica / Micro Focus infoprior to that Hewlett Packard
Initial release200720092005
Current release9.3.1, December 20194.2.2, December 2019Vertica Analytics Platform 9.2.x, March 2019
License infoCommercial or Open SourceOpen Source infoBSD licenseOpen Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenono infoMongoDB available as DBaaS (MongoDB Atlas)no infoavailable on Amazon AWS and Microsoft Azure
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
MongoDB Atlas: Deploy a fully managed cloud database on-demand and ready for use in minutes. Available on AWS, Azure, and GCP.
Implementation languageJavaC++
Server operating systemsLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeschema-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.yes infoUnstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateno infoXQuery supports typesyes infostring, integer, double, decimal, boolean, date, object_id, geospatialyes
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.yes
Secondary indexesyesyesno infoThe concept of 'projections' can be used instead of indexes.
SQL infoSupport of SQLnoRead-only SQL queries via the MongoDB Connector for BIyes infonearly full SQL99 without support for indexes and triggers
APIs and other access methodsJava API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
proprietary protocol using JSONADO.NET
JDBC
Kafka
ODBC
Proprietary protocol
RESTful HTTP API
Supported programming languagesActionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
Actionscript infoinofficial driver
C
C#
C++
Clojure infoinofficial driver
ColdFusion infoinofficial driver
D infoinofficial driver
Dart infoinofficial driver
Delphi infoinofficial driver
Erlang
Go
Groovy infoinofficial driver
Haskell
Java
JavaScript
Lisp infoinofficial driver
Lua infoinofficial driver
MatLab infoinofficial driver
Perl
PHP
PowerShell infoinofficial driver
Prolog infoinofficial driver
Python
R infoinofficial driver
Ruby
Scala
Smalltalk infoinofficial driver
C++
Java
Perl
Python
R
Server-side scripts infoStored proceduresyesJavaScriptyes
Triggersyes infovia eventsyes infoin MongoDB Atlas onlyno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infopartitioned by hashed, ranged, or zoned sharding keysSharding infoSegmentation, Projection Segmentation, Hash Segmentation
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMaster-slave replicationMaster-master replication infoCluster level and Object level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infowith Vertica Connector for Hadoop
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Immediate Consistency
Foreign keys infoReferential integritynono infotypically not used, however similar functionality with DBRef possibleyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datamultiple readers, single writerMulti-document ACID Transactions with snapshot isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infooptionalyes
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 3.2
User concepts infoAccess controlUsers with fine-grained authorization concept on 4 levelsAccess rights for users and rolesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
BaseXMongoDBVertica infoVertica Analytics Platform
Specific characteristicsMongoDB is the leading modern, general purpose data platform, designed to unleash...
» more
Columnar storage, MPP, Hybrid storage model, Aggressive data compression, High availability,...
» more
Competitive advantagesThe MongoDB Data Platform can be used by developers building OLTP and analytical...
» more
Performance at exabyte scale, Deploy anywhere, Open source innovation, Analysis in...
» more
Typical application scenariosInternet of Things and Time Series (Bosch, Jaguar Land Rover) Mobile (The Weather...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metrics70 million downloads (growing at more than 30 thousand downloads per day). 15,000+...
» more
Licensing and pricing modelsMongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more
Cost-based models and subscription-based models are available
» 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.

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

More resources
BaseXMongoDBVertica infoVertica Analytics Platform
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