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DBMS > Google Cloud Datastore vs. Microsoft Access vs. MySQL vs. Prometheus

System Properties Comparison Google Cloud Datastore vs. Microsoft Access vs. MySQL vs. Prometheus

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMySQL  Xexclude from comparisonPrometheus  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Widely used open source RDBMSOpen-source Time Series DBMS and monitoring system
Primary database modelDocument storeRelational DBMSRelational DBMS infoKey/Value like access via memcached APITime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.87
Rank#78  Overall
#12  Document stores
Score107.93
Rank#11  Overall
#8  Relational DBMS
Score1101.50
Rank#2  Overall
#2  Relational DBMS
Score8.00
Rank#51  Overall
#2  Time Series DBMS
Websitecloud.google.com/­datastorewww.microsoft.com/­en-us/­microsoft-365/­accesswww.mysql.comprometheus.io
Technical documentationcloud.google.com/­datastore/­docsdeveloper.microsoft.com/­en-us/­accessdev.mysql.com/­docprometheus.io/­docs
DeveloperGoogleMicrosoftOracle infosince 2010, originally MySQL AB, then Sun
Initial release2008199219952015
Current release1902 (16.0.11328.20222), March 20198.3.0, January 2024
License infoCommercial or Open Sourcecommercialcommercial infoBundled with Microsoft OfficeOpen Source infoGPL version 2. Commercial licenses with extended functionallity are availableOpen Source infoApache 2.0
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.
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++Go
Server operating systemshostedWindows infoNot a real database server, but making use of DLLsFreeBSD
Linux
OS X
Solaris
Windows
Linux
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesNumeric data only
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 infoImport of XML data possible
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query language (GQL)yes infobut not compliant to any SQL standardyes infowith proprietary extensionsno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
ODBC
Proprietary native API
RESTful HTTP/JSON API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresusing Google App Engineyes infosince Access 2010 using the ACE-engineyes infoproprietary syntaxno
TriggersCallbacks using the Google Apps Engineyes infosince Access 2010 using the ACE-engineyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning, sharding with MySQL Cluster or MySQL FabricSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosnoneMulti-source replication
Source-replica replication
yes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
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 Consistencynone
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infobut no files for transaction loggingACID infonot for MyISAM storage engineno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no infoa simple user-level security was built in till version Access 2003Users with fine-grained authorization concept infono user groups or rolesno

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More resources
Google Cloud DatastoreMicrosoft AccessMySQLPrometheus
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