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DBMS > Google Cloud Datastore vs. Kinetica vs. Microsoft Azure Table Storage vs. OpenEdge vs. Realm

System Properties Comparison Google Cloud Datastore vs. Kinetica vs. Microsoft Azure Table Storage vs. OpenEdge vs. Realm

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOpenEdge  Xexclude from comparisonRealm  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsA Wide Column Store for rapid development using massive semi-structured datasetsApplication development environment with integrated database management systemA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelDocument storeRelational DBMSWide column storeRelational DBMSDocument store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score3.51
Rank#86  Overall
#46  Relational DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Websitecloud.google.com/­datastorewww.kinetica.comazure.microsoft.com/­en-us/­services/­storage/­tableswww.progress.com/­openedgerealm.io
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comdocumentation.progress.com/­output/­ua/­OpenEdge_latestrealm.io/­docs
DeveloperGoogleKineticaMicrosoftProgress Software CorporationRealm, acquired by MongoDB in May 2019
Initial release20082012201219842014
Current release7.1, August 2021OpenEdge 12.2, March 2020
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++
Server operating systemshostedLinuxhostedAIX
HP-UX
Linux
Solaris
Windows
Android
Backend: server-less
iOS
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyesyes
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.nononoyesno
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsnoyes infoclose to SQL 92no
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Progress proprietary ABL (Advanced Business Language).Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsnoyesno inforuns within the applications so server-side scripts are unnecessary
TriggersCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangenoyesyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning infosince Version 11.4none
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnone
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 Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnooptimistic lockingACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMnonoyes infoIn-Memory realm
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelAccess rights based on private key authentication or shared access signaturesUsers and groupsyes

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More resources
Google Cloud DatastoreKineticaMicrosoft Azure Table StorageOpenEdgeRealm
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