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DBMS > EsgynDB vs. JanusGraph vs. MongoDB

System Properties Comparison EsgynDB vs. JanusGraph vs. MongoDB

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonMongoDB  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelRelational DBMSGraph 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
Score0.30
Rank#269  Overall
#126  Relational DBMS
Score2.36
Rank#112  Overall
#7  Graph DBMS
Score496.16
Rank#5  Overall
#1  Document stores
Websitewww.esgyn.cnjanusgraph.orgwww.mongodb.com
Technical documentationdocs.janusgraph.orgdocs.mongodb.com/­manual
DeveloperEsgynLinux Foundation; originally developed as Titan by AureliusMongoDB, Inc
Initial release201520172009
Current release0.5.2, May 20205.0, July 2021
License infoCommercial or Open SourcecommercialOpen 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 languageC++, JavaJavaC++
Server operating systemsLinuxLinux
OS X
Unix
Windows
Linux
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 SQLyesnoRead-only SQL queries via the MongoDB Connector for BI
APIs and other access methodsADO.NET
JDBC
ODBC
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
proprietary protocol using JSON
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetClojure
Java
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 proceduresJava Stored ProceduresyesJavaScript
Triggersnoyesyes infoin MongoDB Atlas only
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding 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 replication between multi datacentersyesMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infovia Faunus, a graph analytics engineyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integrityyesyes infoRelationships in graphsno infotypically not used, however similar functionality with DBRef possible
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDMulti-document ACID Transactions with snapshot isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes 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 controlfine grained access rights according to SQL-standardUser authentification and security via Rexster Graph ServerAccess rights for users and roles
More information provided by the system vendor
EsgynDBJanusGraph infosuccessor of TitanMongoDB
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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More resources
EsgynDBJanusGraph infosuccessor of TitanMongoDB
DB-Engines blog posts

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Conferences and events

Introduction to MongoDB
11 am ET | 3 pm GMT | 4 pm BST, 27 July 2021

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