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DBMS > Google Cloud Datastore vs. Microsoft Access vs. Oracle Berkeley DB vs. Oracle Coherence

System Properties Comparison Google Cloud Datastore vs. Microsoft Access vs. Oracle Berkeley DB vs. Oracle Coherence

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonOracle Coherence  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 in-process key-value storeOracles in-memory data grid solution
Primary database modelDocument storeRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score1.92
Rank#130  Overall
#22  Key-value stores
Websitecloud.google.com/­datastorewww.microsoft.com/­en-us/­microsoft-365/­accesswww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.oracle.com/­java/­coherence
Technical documentationcloud.google.com/­datastore/­docsdeveloper.microsoft.com/­en-us/­accessdocs.oracle.com/­cd/­E17076_05/­html/­index.htmldocs.oracle.com/­en/­middleware/­standalone/­coherence
DeveloperGoogleMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleOracle
Initial release2008199219942007
Current release1902 (16.0.11328.20222), March 201918.1.40, May 202014.1, August 2023
License infoCommercial or Open Sourcecommercialcommercial infoBundled with Microsoft OfficeOpen Source infocommercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, Java, C++ (depending on the Berkeley DB edition)Java
Server operating systemshostedWindows infoNot a real database server, but making use of DLLsAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
All OS with a Java VM
Data schemeschema-freeyesschema-freeschema-free
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.noyes infoonly with the Berkeley DB XML editionno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query language (GQL)yes infobut not compliant to any SQL standardyes infoSQL interfaced based on SQLite is availableno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DAO
ODBC
OLE DB
JCache
JPA
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
.Net
C++
Java
Server-side scripts infoStored proceduresusing Google App Engineyes infosince Access 2010 using the ACE-enginenono
TriggersCallbacks using the Google Apps Engineyes infosince Access 2010 using the ACE-engineyes infoonly for the SQL APIyes infoLive Events
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosnoneSource-replica replicationyes, with selectable consistency level
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.Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnono
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 loggingACIDconfigurable
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyesyes infooptionally
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
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 2003noauthentification to access the cache via certificates or http basic authentication

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More resources
Google Cloud DatastoreMicrosoft AccessOracle Berkeley DBOracle Coherence
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