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DBMS > Google Cloud Datastore vs. Microsoft Azure Table Storage vs. OpenTSDB vs. Teradata Aster vs. TinkerGraph

System Properties Comparison Google Cloud Datastore vs. Microsoft Azure Table Storage vs. OpenTSDB vs. Teradata Aster vs. TinkerGraph

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOpenTSDB  Xexclude from comparisonTeradata Aster  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 PlatformA Wide Column Store for rapid development using massive semi-structured datasetsScalable Time Series DBMS based on HBasePlatform for big data analytics on multistructured data sources and typesA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelDocument storeWide column storeTime Series DBMSRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.49
Rank#79  Overall
#12  Document stores
Score4.92
Rank#73  Overall
#6  Wide column stores
Score1.73
Rank#147  Overall
#12  Time Series DBMS
Score0.12
Rank#344  Overall
#34  Graph DBMS
Websitecloud.google.com/­datastoreazure.microsoft.com/­en-us/­services/­storage/­tablesopentsdb.nettinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationcloud.google.com/­datastore/­docsopentsdb.net/­docs/­build/­html/­index.html
DeveloperGoogleMicrosoftcurrently maintained by Yahoo and other contributorsTeradata
Initial release20082012201120052009
License infoCommercial or Open SourcecommercialcommercialOpen Source infoLGPLcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemshostedhostedLinux
Windows
Linux
Data schemeschema-freeschema-freeschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeschema-free
Typing infopredefined data types such as float or dateyes, details hereyesnumeric data for metrics, strings for tagsyesyes
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 infoin Aster File Storeno
Secondary indexesyesnonoyesno
SQL infoSupport of SQLSQL-like query language (GQL)nonoyesno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIHTTP API
Telnet API
ADO.NET
JDBC
ODBC
OLE DB
TinkerPop 3
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Erlang
Go
Java
Python
R
Ruby
C
C#
C++
Java
Python
R
Groovy
Java
Server-side scripts infoStored proceduresusing Google App EnginenonoR packagesno
TriggersCallbacks using the Google Apps Enginenononono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infobased on HBaseShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infobased on HBaseyes 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 Dataflownonoyes infoSQL Map-Reduce Frameworkno
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 infobased on HBaseImmediate Consistency or Eventual Consistency depending on configurationnone
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic lockingnoACIDno
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)Access rights based on private key authentication or shared access signaturesnofine grained access rights according to SQL-standardno

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More resources
Google Cloud DatastoreMicrosoft Azure Table StorageOpenTSDBTeradata AsterTinkerGraph
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