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DBMS > Google Cloud Datastore vs. Immudb vs. Microsoft Access vs. Oracle Coherence vs. TerarkDB

System Properties Comparison Google Cloud Datastore vs. Immudb vs. Microsoft Access vs. Oracle Coherence vs. TerarkDB

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonImmudb  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonOracle Coherence  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.Microsoft 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.)Oracles in-memory data grid solutionA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelDocument storeKey-value storeRelational DBMSKey-value storeKey-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.24
Rank#305  Overall
#43  Key-value stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score1.92
Rank#130  Overall
#22  Key-value stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitecloud.google.com/­datastoregithub.com/­codenotary/­immudb
immudb.io
www.microsoft.com/­en-us/­microsoft-365/­accesswww.oracle.com/­java/­coherencegithub.com/­bytedance/­terarkdb
Technical documentationcloud.google.com/­datastore/­docsdocs.immudb.iodeveloper.microsoft.com/­en-us/­accessdocs.oracle.com/­en/­middleware/­standalone/­coherencebytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperGoogleCodenotaryMicrosoftOracleByteDance, originally Terark
Initial release20082020199220072016
Current release1.2.3, April 20221902 (16.0.11328.20222), March 201914.1, August 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial infoBundled with Microsoft Officecommercialcommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++JavaC++
Server operating systemshostedBSD
Linux
macOS
Solaris
Windows
z/OS
Windows infoNot a real database server, but making use of DLLsAll OS with a Java VM
Data schemeschema-freeschema-freeyesschema-freeschema-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.nononono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like syntaxyes infobut not compliant to any SQL standardnono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
gRPC protocol
PostgreSQL wire protocol
ADO.NET
DAO
ODBC
OLE DB
JCache
JPA
RESTful HTTP API
C++ API
Java API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C++
Java
C++
Java
Server-side scripts infoStored proceduresusing Google App Enginenoyes infosince Access 2010 using the ACE-enginenono
TriggersCallbacks using the Google Apps Enginenoyes infosince Access 2010 using the ACE-engineyes infoLive Eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosnoneyes, with selectable consistency levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononono
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 ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesnono
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 loggingconfigurableno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyes infooptionallyyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
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 2003authentification to access the cache via certificates or http basic authenticationno

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More resources
Google Cloud DatastoreImmudbMicrosoft AccessOracle CoherenceTerarkDB
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