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DBMS > Google Cloud Datastore vs. Microsoft SQL Server vs. MySQL vs. TigerGraph

System Properties Comparison Google Cloud Datastore vs. Microsoft SQL Server vs. MySQL vs. TigerGraph

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonMySQL  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMicrosofts flagship relational DBMSWidely used open source RDBMSA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument storeRelational DBMSRelational DBMS infoKey/Value like access via memcached APIGraph DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score824.29
Rank#3  Overall
#3  Relational DBMS
Score1083.74
Rank#2  Overall
#2  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitecloud.google.com/­datastorewww.microsoft.com/­en-us/­sql-serverwww.mysql.comwww.tigergraph.com
Technical documentationcloud.google.com/­datastore/­docslearn.microsoft.com/­en-US/­sql/­sql-serverdev.mysql.com/­docdocs.tigergraph.com
DeveloperGoogleMicrosoftOracle infosince 2010, originally MySQL AB, then Sun
Initial release2008198919952017
Current releaseSQL Server 2022, November 20228.4.0, April 2024
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availableOpen Source infoGPL version 2. Commercial licenses with extended functionallity are availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.
Implementation languageC++C and C++C++
Server operating systemshostedLinux
Windows
FreeBSD
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
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.noyesyesno
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)yesyes infowith proprietary extensionsSQL-like query language (GSQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
ADO.NET
JDBC
ODBC
Proprietary native API
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C++
Java
Server-side scripts infoStored proceduresusing Google App EngineTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javayes infoproprietary syntaxyes
TriggersCallbacks using the Google Apps Engineyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingtables can be distributed across several files (horizontal partitioning); sharding through federationhorizontal partitioning, sharding with MySQL Cluster or MySQL Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes, but depending on the SQL-Server EditionMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonoyes
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
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesyes infonot for MyISAM storage engineyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID infonot for MyISAM storage engineACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
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-standardUsers with fine-grained authorization concept infono user groups or rolesRole-based access control

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More resources
Google Cloud DatastoreMicrosoft SQL ServerMySQLTigerGraph
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