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DBMS > Google Cloud Datastore vs. Hawkular Metrics vs. Hazelcast vs. RDF4J

System Properties Comparison Google Cloud Datastore vs. Hawkular Metrics vs. Hazelcast vs. RDF4J

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHazelcast  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A widely adopted in-memory data gridRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument storeTime Series DBMSKey-value storeRDF store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#71  Overall
#12  Document stores
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Score5.72
Rank#59  Overall
#6  Key-value stores
Score0.72
Rank#222  Overall
#9  RDF stores
Websitecloud.google.com/­datastorewww.hawkular.orghazelcast.comrdf4j.org
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidehazelcast.org/­imdg/­docsrdf4j.org/­documentation
DeveloperGoogleCommunity supported by Red HatHazelcastSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008201420082004
Current release5.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoEclipse Distribution License (EDL), v1.0.
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 languageJavaJavaJava
Server operating systemshostedLinux
OS X
Windows
All OS with a Java VMLinux
OS X
Unix
Windows
Data schemeschema-freeschema-freeschema-freeyes infoRDF Schemas
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.nonoyes infothe object must implement a serialization strategy
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query language (GQL)noSQL-like query languageno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTJCache
JPA
Memcached protocol
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Java
PHP
Python
Server-side scripts infoStored proceduresusing Google App Enginenoyes infoEvent Listeners, Executor Servicesyes
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on Cassandrayes infoReplicated Mapnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyesno
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 infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnoone or two-phase-commit; repeatable reads; read commitedACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noRole-based access controlno

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More resources
Google Cloud DatastoreHawkular MetricsHazelcastRDF4J infoformerly known as Sesame
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