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DBMS > Google Cloud Datastore vs. JanusGraph vs. MonetDB vs. Tkrzw

System Properties Comparison Google Cloud Datastore vs. JanusGraph vs. MonetDB vs. Tkrzw

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonMonetDB  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017A relational database management system that stores data in columnsA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument storeGraph DBMSRelational DBMSKey-value store
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score2.02
Rank#125  Overall
#12  Graph DBMS
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitecloud.google.com/­datastorejanusgraph.orgwww.monetdb.orgdbmx.net/­tkrzw
Technical documentationcloud.google.com/­datastore/­docsdocs.janusgraph.orgwww.monetdb.org/­Documentation
DeveloperGoogleLinux Foundation; originally developed as Titan by AureliusMonetDB BVMikio Hirabayashi
Initial release2008201720042020
Current release0.6.3, February 2023Dec2023 (11.49), December 20230.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoMozilla Public License 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC++
Server operating systemshostedLinux
OS X
Unix
Windows
FreeBSD
Linux
OS X
Solaris
Windows
Linux
macOS
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesno
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.nonono
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)noyes infoSQL 2003 with some extensionsno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Python
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresusing Google App Engineyesyes, in SQL, C, Rno
TriggersCallbacks using the Google Apps Engineyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding via remote tablesnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyesnone infoSource-replica replication available in experimental statusnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes infovia Faunus, a graph analytics enginenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyes infoRelationships in graphsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)User authentification and security via Rexster Graph Serverfine grained access rights according to SQL-standardno

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More resources
Google Cloud DatastoreJanusGraph infosuccessor of TitanMonetDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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