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DBMS > Google Cloud Datastore vs. Hypertable vs. Microsoft Azure SQL Database vs. Titan

System Properties Comparison Google Cloud Datastore vs. Hypertable vs. Microsoft Azure SQL Database vs. Titan

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHypertable  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonTitan  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn open source BigTable implementation based on distributed file systems such as HadoopDatabase as a Service offering with high compatibility to Microsoft SQL ServerTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelDocument storeWide column storeRelational DBMSGraph DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score77.99
Rank#16  Overall
#11  Relational DBMS
Websitecloud.google.com/­datastoreazure.microsoft.com/­en-us/­products/­azure-sql/­databasegithub.com/­thinkaurelius/­titan
Technical documentationcloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqlgithub.com/­thinkaurelius/­titan/­wiki
DeveloperGoogleHypertable Inc.MicrosoftAurelius, owned by DataStax
Initial release2008200920102012
Current release0.9.8.11, March 2016V12
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availablecommercialOpen Source infoApache license, version 2.0
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 languageC++C++Java
Server operating systemshostedLinux
OS X
Windows infoan inofficial Windows port is available
hostedLinux
OS X
Unix
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details herenoyesyes
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
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesyes
SQL infoSupport of SQLSQL-like query language (GQL)noyesno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
C++ API
Thrift
ADO.NET
JDBC
ODBC
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Python
Server-side scripts infoStored proceduresusing Google App EnginenoTransact SQLyes
TriggersCallbacks using the Google Apps Enginenoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor on file system levelyes, with always 3 replicas availableyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnoyes infovia Faunus, a graph analytics engine
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 ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standardUser authentification and security via Rexster Graph Server

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More resources
Google Cloud DatastoreHypertableMicrosoft Azure SQL Database infoformerly SQL AzureTitan
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