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DBMS > Google Cloud Datastore vs. JanusGraph vs. Microsoft Azure Table Storage vs. Oracle Berkeley DB

System Properties Comparison Google Cloud Datastore vs. JanusGraph vs. Microsoft Azure Table Storage vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOracle Berkeley DB  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 Wide Column Store for rapid development using massive semi-structured datasetsWidely used in-process key-value store
Primary database modelDocument storeGraph DBMSWide column storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
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
Score4.04
Rank#77  Overall
#6  Wide column stores
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Websitecloud.google.com/­datastorejanusgraph.orgazure.microsoft.com/­en-us/­services/­storage/­tableswww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationcloud.google.com/­datastore/­docsdocs.janusgraph.orgdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperGoogleLinux Foundation; originally developed as Titan by AureliusMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2008201720121994
Current release0.6.3, February 202318.1.40, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedLinux
OS X
Unix
Windows
hostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeschema-freeyesschema-freeschema-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.nononoyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query language (GQL)nonoyes infoSQL interfaced based on SQLite is available
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresusing Google App Engineyesnono
TriggersCallbacks using the Google Apps Engineyesnoyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
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 graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.nonoyes
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 ServerAccess rights based on private key authentication or shared access signaturesno

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More resources
Google Cloud DatastoreJanusGraph infosuccessor of TitanMicrosoft Azure Table StorageOracle Berkeley DB
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