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DBMS > Google Cloud Datastore vs. Hazelcast vs. MonetDB vs. Percona Server for MongoDB

System Properties Comparison Google Cloud Datastore vs. Hazelcast vs. MonetDB vs. Percona Server for MongoDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHazelcast  Xexclude from comparisonMonetDB  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA widely adopted in-memory data gridA relational database management system that stores data in columnsA drop-in replacement for MongoDB Community Edition with enterprise-grade features.
Primary database modelDocument storeKey-value storeRelational DBMSDocument store
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score0.60
Rank#246  Overall
#39  Document stores
Websitecloud.google.com/­datastorehazelcast.comwww.monetdb.orgwww.percona.com/­mongodb/­software/­percona-server-for-mongodb
Technical documentationcloud.google.com/­datastore/­docshazelcast.org/­imdg/­docswww.monetdb.org/­Documentationdocs.percona.com/­percona-distribution-for-mongodb
DeveloperGoogleHazelcastMonetDB BVPercona
Initial release2008200820042015
Current release5.3.6, November 2023Dec2023 (11.49), December 20233.4.10-2.10, November 2017
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoMozilla Public License 2.0Open Source infoGPL Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC++
Server operating systemshostedAll OS with a Java VMFreeBSD
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
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 infothe object must implement a serialization strategyno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query languageyes infoSQL 2003 with some extensionsno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
proprietary protocol using JSON
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
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
Server-side scripts infoStored proceduresusing Google App Engineyes infoEvent Listeners, Executor Servicesyes, in SQL, C, RJavaScript
TriggersCallbacks using the Google Apps Engineyes infoEventsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding via remote tablesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infoReplicated Mapnone infoSource-replica replication available in experimental statusSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnoyes
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 selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate 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 Transactionsone or two-phase-commit; repeatable reads; read commitedACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infovia In-Memory Engine
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlfine grained access rights according to SQL-standardAccess rights for users and roles

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More resources
Google Cloud DatastoreHazelcastMonetDBPercona Server for MongoDB
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