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DBMS > Google Cloud Datastore vs. Microsoft Azure SQL Database vs. NSDb vs. Teradata Aster vs. Yaacomo

System Properties Comparison Google Cloud Datastore vs. Microsoft Azure SQL Database vs. NSDb vs. Teradata Aster vs. Yaacomo

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonNSDb  Xexclude from comparisonTeradata Aster  Xexclude from comparisonYaacomo  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
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 KubernetesPlatform for big data analytics on multistructured data sources and typesOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument storeRelational DBMSTime Series DBMSRelational DBMSRelational 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.ioyaacomo.com
Technical documentationcloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqlnsdb.io/­Architecture
DeveloperGoogleMicrosoftTeradataQ2WEB GmbH
Initial release20082010201720052009
Current releaseV12
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0commercialcommercial
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 languageC++Java, Scala
Server operating systemshostedhostedLinux
macOS
LinuxAndroid
Linux
Windows
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 Storeyes
Typing infopredefined data types such as float or dateyes, details hereyesyes: int, bigint, decimal, stringyesyes
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.noyesnoyes infoin Aster File Storeno
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-like query language (GQL)yesSQL-like query languageyesyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
gRPC
HTTP REST
WebSocket
ADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresusing Google App EngineTransact SQLnoR packages
TriggersCallbacks using the Google Apps Engineyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes, with always 3 replicas availableyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.Source-replica replication
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 ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
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-standardfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreMicrosoft Azure SQL Database infoformerly SQL AzureNSDbTeradata AsterYaacomo
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