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DBMS > Google Cloud Datastore vs. Microsoft Access vs. PouchDB vs. VoltDB

System Properties Comparison Google Cloud Datastore vs. Microsoft Access vs. PouchDB vs. VoltDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonPouchDB  Xexclude from comparisonVoltDB  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.)JavaScript DBMS with an API inspired by CouchDBDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelDocument storeRelational DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score1.47
Rank#157  Overall
#73  Relational DBMS
Websitecloud.google.com/­datastorewww.microsoft.com/­en-us/­microsoft-365/­accesspouchdb.comwww.voltdb.com
Technical documentationcloud.google.com/­datastore/­docsdeveloper.microsoft.com/­en-us/­accesspouchdb.com/­guidesdocs.voltdb.com
DeveloperGoogleMicrosoftApache Software FoundationVoltDB Inc.
Initial release2008199220122010
Current release1902 (16.0.11328.20222), March 20197.1.1, June 201911.3, April 2022
License infoCommercial or Open Sourcecommercialcommercial infoBundled with Microsoft OfficeOpen SourceOpen Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
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.
Implementation languageC++JavaScriptJava, C++
Server operating systemshostedWindows infoNot a real database server, but making use of DLLsserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X infofor development
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyesnoyes
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.nono
Secondary indexesyesyesyes infovia viewsyes
SQL infoSupport of SQLSQL-like query language (GQL)yes infobut not compliant to any SQL standardnoyes infoonly a subset of SQL 99
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DAO
ODBC
OLE DB
HTTP REST infoonly for PouchDB Server
JavaScript API
Java API
JDBC
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
JavaScriptC#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresusing Google App Engineyes infosince Access 2010 using the ACE-engineView functions in JavaScriptJava
TriggersCallbacks using the Google Apps Engineyes infosince Access 2010 using the ACE-engineyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infowith a proxy-based framework, named couchdb-loungeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosnoneMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyesno
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.Eventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnono infoFOREIGN KEY constraints are not supported
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 loggingnoACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyes infoby using IndexedDB, WebSQL or LevelDB as backendyes infoSnapshots and command logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
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 2003noUsers and roles with access to stored procedures

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More resources
Google Cloud DatastoreMicrosoft AccessPouchDBVoltDB
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