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DBMS > Google Cloud Datastore vs. HBase vs. JanusGraph vs. Postgres-XL

System Properties Comparison Google Cloud Datastore vs. HBase vs. JanusGraph vs. Postgres-XL

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NameGoogle Cloud Datastore  Xexclude from comparisonHBase  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWide-column store based on Apache Hadoop and on concepts of BigTableA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Based on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelDocument storeWide column storeGraph DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websitecloud.google.com/­datastorehbase.apache.orgjanusgraph.orgwww.postgres-xl.org
Technical documentationcloud.google.com/­datastore/­docshbase.apache.org/­book.htmldocs.janusgraph.orgwww.postgres-xl.org/­documentation
DeveloperGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetLinux Foundation; originally developed as Titan by Aurelius
Initial release2008200820172014 infosince 2012, originally named StormDB
Current release2.3.4, January 20210.6.3, February 202310 R1, October 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoMozilla public license
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
Linux
OS X
Unix
Windows
Linux
macOS
Data schemeschema-freeschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateyes, details hereoptions to bring your own types, AVROyesyes
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 infoXML type, but no XML query functionality
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query language (GQL)nonoyes infodistributed, parallel query execution
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
Clojure
Java
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresusing Google App Engineyes infoCoprocessors in Javayesuser defined functions
TriggersCallbacks using the Google Apps Engineyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesyes infovia Faunus, a graph analytics engineno
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.Immediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsSingle row ACID (across millions of columns)ACIDACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACUser authentification and security via Rexster Graph Serverfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreHBaseJanusGraph infosuccessor of TitanPostgres-XL
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