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DBMS > Google Cloud Datastore vs. Heroic vs. InterSystems IRIS vs. Percona Server for MongoDB vs. Tkrzw

System Properties Comparison Google Cloud Datastore vs. Heroic vs. InterSystems IRIS vs. Percona Server for MongoDB vs. Tkrzw

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHeroic  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilityA drop-in replacement for MongoDB Community Edition with enterprise-grade features.A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument storeTime Series DBMSDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Document storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score3.54
Rank#84  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Score0.60
Rank#246  Overall
#39  Document stores
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitecloud.google.com/­datastoregithub.com/­spotify/­heroicwww.intersystems.com/­products/­intersystems-iriswww.percona.com/­mongodb/­software/­percona-server-for-mongodbdbmx.net/­tkrzw
Technical documentationcloud.google.com/­datastore/­docsspotify.github.io/­heroicdocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clsdocs.percona.com/­percona-distribution-for-mongodb
DeveloperGoogleSpotifyInterSystemsPerconaMikio Hirabayashi
Initial release20082014201820152020
Current release2023.3, June 20233.4.10-2.10, November 20170.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoGPL Version 2Open Source infoApache Version 2.0
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 languageJavaC++C++
Server operating systemshostedAIX
Linux
macOS
Ubuntu
Windows
LinuxLinux
macOS
Data schemeschema-freeschema-freedepending on used data modelschema-freeschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesyesno
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.nonoyesnono
Secondary indexesyesyes infovia Elasticsearchyesyes
SQL infoSupport of SQLSQL-like query language (GQL)noyesnono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
RESTful HTTP API
proprietary protocol using JSON
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Java
JavaScript (Node.js)
Python
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresusing Google App EnginenoyesJavaScriptno
TriggersCallbacks using the Google Apps Enginenoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosyesSource-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonoyesno
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
Immediate ConsistencyEventual Consistency
Immediate 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 TransactionsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nonoyesyes infovia In-Memory Engineyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesAccess rights for users and rolesno
More information provided by the system vendor
Google Cloud DatastoreHeroicInterSystems IRISPercona Server for MongoDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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Google Cloud DatastoreHeroicInterSystems IRISPercona Server for MongoDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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