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DBMS > Google Cloud Datastore vs. JanusGraph vs. LeanXcale vs. Microsoft Access

System Properties Comparison Google Cloud Datastore vs. JanusGraph vs. LeanXcale vs. Microsoft Access

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Access  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 highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)
Primary database modelDocument storeGraph DBMSKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Websitecloud.google.com/­datastorejanusgraph.orgwww.leanxcale.comwww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationcloud.google.com/­datastore/­docsdocs.janusgraph.orgdeveloper.microsoft.com/­en-us/­access
DeveloperGoogleLinux Foundation; originally developed as Titan by AureliusLeanXcaleMicrosoft
Initial release2008201720151992
Current release0.6.3, February 20231902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial infoBundled with Microsoft Office
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 languageJavaC++
Server operating systemshostedLinux
OS X
Unix
Windows
Windows infoNot a real database server, but making use of DLLs
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyes
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-like query language (GQL)noyes infothrough Apache Derbyyes infobut not compliant to any SQL standard
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
ADO.NET
DAO
ODBC
OLE DB
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Python
C
Java
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresusing Google App Engineyesyes infosince Access 2010 using the ACE-engine
TriggersCallbacks using the Google Apps Engineyesyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)none
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyesnone
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 graphsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyesyes infobut no files for transaction logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
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 Serverno infoa simple user-level security was built in till version Access 2003

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More resources
Google Cloud DatastoreJanusGraph infosuccessor of TitanLeanXcaleMicrosoft Access
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