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DBMS > Google Cloud Datastore vs. GridGain vs. Microsoft Access vs. Yanza

System Properties Comparison Google Cloud Datastore vs. GridGain vs. Microsoft Access vs. Yanza

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformGridGain is an in-memory computing platform, built on Apache IgniteMicrosoft 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.)Time Series DBMS for IoT Applications
Primary database modelDocument storeColumnar
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#71  Overall
#12  Document stores
Score1.48
Rank#150  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#69  Relational DBMS
Score93.76
Rank#12  Overall
#8  Relational DBMS
Websitecloud.google.com/­datastorewww.gridgain.comwww.microsoft.com/­en-us/­microsoft-365/­accessyanza.com
Technical documentationcloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.htmldeveloper.microsoft.com/­en-us/­access
DeveloperGoogleGridGain Systems, Inc.MicrosoftYanza
Initial release2008200719922015
Current releaseGridGain 8.5.11902 (16.0.11328.20222), March 2019
License infoCommercial or Open Sourcecommercialcommercial, open sourcecommercial infoBundled with Microsoft Officecommercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesnonono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .Net, Python, REST, SQLC++
Server operating systemshostedLinux
OS X
Solaris
Windows
z/OS
Windows infoNot a real database server, but making use of DLLsWindows
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesno
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
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLyes infobut not compliant to any SQL standardno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
DAO
ODBC
OLE DB
HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
any language that supports HTTP calls
Server-side scripts infoStored proceduresusing Google App Engineyes (compute grid and cache interceptors can be used instead)yes infosince Access 2010 using the ACE-engineno
TriggersCallbacks using the Google Apps Engineyes (cache interceptors and events)yes infosince Access 2010 using the ACE-engineyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes (replicated cache)nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)nono
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 pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID infobut no files for transaction loggingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyes
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)Role-based access control
Security Hooks for custom implementations
no infoa simple user-level security was built in till version Access 2003no

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More resources
Google Cloud DatastoreGridGainMicrosoft AccessYanza
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