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DBMS > Apache Druid vs. Dgraph vs. MongoDB

System Properties Comparison Apache Druid vs. Dgraph vs. MongoDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDgraph  Xexclude from comparisonMongoDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDistributed and scalable native Graph DBMSOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelRelational DBMS
Time Series DBMS
Graph 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
Score3.27
Rank#93  Overall
#48  Relational DBMS
#6  Time Series DBMS
Score1.81
Rank#127  Overall
#10  Graph DBMS
Score496.50
Rank#5  Overall
#1  Document stores
Websitedruid.apache.orgdgraph.iowww.mongodb.com
Technical documentationdruid.apache.org/­docs/­latest/­designdgraph.io/­docsdocs.mongodb.com/­manual
DeveloperApache Software Foundation and contributorsDgraph Labs, Inc.MongoDB, Inc
Initial release201220162009
Current release0.21.0, April 20215.0, July 2021
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache 2.0Open 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

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Implementation languageJavaGoC++
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedschema-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.
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 SQLSQL for queryingnoRead-only SQL queries via the MongoDB Connector for BI
APIs and other access methodsJDBC
RESTful HTTP/JSON API
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
proprietary protocol using JSON
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
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 proceduresnonoJavaScript
Triggersnonoyes infoin MongoDB Atlas only
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedyesSharding 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 nodesyes, via HDFS, S3 or other storage enginesSynchronous replication via RaftMulti-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 systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynonono infotypically not used, however similar functionality with DBRef possible
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDMulti-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 infoIn-memory storage engine introduced with MongoDB version 3.2
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemno infoPlanned for future releasesAccess rights for users and roles
More information provided by the system vendor
Apache DruidDgraphMongoDB
Specific characteristicsMongoDB’s application data platform provides developers a unified interface to power...
» more
Competitive advantagesHorizontally scalable transactional graph database with fast arbitrary-depth joins...
» more
The 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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More resources
Apache DruidDgraphMongoDB
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Conferences and events

MongoDB.Local London
London, 9 November 2021

Finished events

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

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