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DBMS > Google Cloud Datastore vs. Postgres-XL vs. Teradata Aster vs. TigerGraph vs. TinkerGraph

System Properties Comparison Google Cloud Datastore vs. Postgres-XL vs. Teradata Aster vs. TigerGraph vs. TinkerGraph

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonPostgres-XL  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTigerGraph  Xexclude from comparisonTinkerGraph  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresPlatform for big data analytics on multistructured data sources and typesA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelDocument storeRelational DBMSRelational DBMSGraph DBMSGraph DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.49
Rank#79  Overall
#12  Document stores
Score0.52
Rank#256  Overall
#117  Relational DBMS
Score1.83
Rank#141  Overall
#13  Graph DBMS
Score0.12
Rank#344  Overall
#34  Graph DBMS
Websitecloud.google.com/­datastorewww.postgres-xl.orgwww.tigergraph.comtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationcloud.google.com/­datastore/­docswww.postgres-xl.org/­documentationdocs.tigergraph.com
DeveloperGoogleTeradata
Initial release20082014 infosince 2012, originally named StormDB200520172009
Current release10 R1, October 2018
License infoCommercial or Open SourcecommercialOpen Source infoMozilla public licensecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++Java
Server operating systemshostedLinux
macOS
LinuxLinux
Data schemeschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyesschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesyesyes
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.noyes infoXML type, but no XML query functionalityyes infoin Aster File Storenono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query language (GQL)yes infodistributed, parallel query executionyesSQL-like query language (GSQL)no
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
OLE DB
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
TinkerPop 3
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Java
Python
R
C++
Java
Groovy
Java
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsR packagesyesno
TriggersCallbacks using the Google Apps Engineyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyes infoSQL Map-Reduce Frameworkyesno
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 ConsistencyImmediate Consistency or Eventual Consistency depending on configurationnone
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnoyes infoRelationships in graphsyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoMVCCACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesno
Durability infoSupport for making data persistentyesyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonononoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardfine grained access rights according to SQL-standardRole-based access controlno

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More resources
Google Cloud DatastorePostgres-XLTeradata AsterTigerGraphTinkerGraph
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