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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonNSDb  Xexclude from comparisonTitan  Xexclude from comparison
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 PlatformDatabase as a Service offering with high compatibility to Microsoft SQL ServerScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelDocument storeRelational DBMSTime Series 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
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Websitecloud.google.com/­datastoreazure.microsoft.com/­en-us/­products/­azure-sql/­databasensdb.iogithub.com/­thinkaurelius/­titan
Technical documentationcloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqlnsdb.io/­Architecturegithub.com/­thinkaurelius/­titan/­wiki
DeveloperGoogleMicrosoftAurelius, owned by DataStax
Initial release2008201020172012
Current releaseV12
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java, ScalaJava
Server operating systemshostedhostedLinux
macOS
Linux
OS X
Unix
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyes: int, bigint, decimal, stringyes
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.noyesno
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query language (GQL)yesSQL-like query languageno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
gRPC
HTTP REST
WebSocket
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Scala
Clojure
Java
Python
Server-side scripts infoStored proceduresusing Google App EngineTransact SQLnoyes
TriggersCallbacks using the Google Apps Engineyesyes
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 Paxosyes, with always 3 replicas availableyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonoyes 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 ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnoyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes 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)fine grained access rights according to SQL-standardUser authentification and security via Rexster Graph Server

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More resources
Google Cloud DatastoreMicrosoft Azure SQL Database infoformerly SQL AzureNSDbTitan
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