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DBMS > Apache Druid vs. MongoDB vs. RocksDB

System Properties Comparison Apache Druid vs. MongoDB vs. RocksDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonMongoDB  Xexclude from comparisonRocksDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureEmbeddable persistent key-value store optimized for fast storage (flash and RAM)
Primary database modelRelational DBMS
Time Series DBMS
Document storeKey-value store
Secondary database modelsSearch engine infointegrated Lucene index, currently in MongoDB Atlas only.
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.66
Rank#104  Overall
#51  Relational DBMS
#7  Time Series DBMS
Score458.95
Rank#5  Overall
#1  Document stores
Score3.20
Rank#94  Overall
#18  Key-value stores
Websitedruid.apache.orgwww.mongodb.comrocksdb.org
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.mongodb.com/­manualgithub.com/­facebook/­rocksdb/­wiki
DeveloperApache Software Foundation and contributorsMongoDB, IncFacebook, Inc.
Initial release201220092013
Current release0.20.1, January 20214.4.3 , December 20206.14.6 , December 2020
License infoCommercial or Open SourceOpen Source infoApache license v2Open 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 infoBSD
Cloud-based only infoOnly available as a cloud servicenono infoMongoDB available as DBaaS (MongoDB Atlas)no
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemsLinux
OS X
Unix
Linux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedschema-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.schema-free
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, decimal, boolean, date, object_id, geospatialno
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 indexesyesyesno
SQL infoSupport of SQLSQL for queryingRead-only SQL queries via the MongoDB Connector for BIno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
proprietary protocol using JSONC++ API
Java API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
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
C++
Java
Server-side scripts infoStored proceduresnoJavaScriptno
Triggersnoyes infoin MongoDB Atlas onlyno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infopartitioned by hashed, ranged, or zoned sharding keysnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynono infotypically not used, however similar functionality with DBRef possibleno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoMulti-document ACID Transactions with snapshot isolationyes
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.noyes infoIn-memory storage engine introduced with MongoDB version 3.2yes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users and rolesno
More information provided by the system vendor
Apache DruidMongoDBRocksDB
Specific characteristicsMongoDB is the leading modern, general purpose data platform, designed to unleash...
» 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 metrics125 million downloads (growing at more than 30 thousand downloads per day), over...
» more
Licensing and pricing modelsMongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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More resources
Apache DruidMongoDBRocksDB
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