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DBMS > etcd vs. Google Cloud Datastore vs. Microsoft Azure Table Storage vs. RDF4J

System Properties Comparison etcd vs. Google Cloud Datastore vs. Microsoft Azure Table Storage vs. RDF4J

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionA distributed reliable key-value storeAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Wide Column Store for rapid development using massive semi-structured datasetsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelKey-value storeDocument storeWide column storeRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.05
Rank#53  Overall
#5  Key-value stores
Score4.13
Rank#71  Overall
#12  Document stores
Score3.55
Rank#80  Overall
#6  Wide column stores
Score0.72
Rank#222  Overall
#9  RDF stores
Websiteetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­datastoreazure.microsoft.com/­en-us/­services/­storage/­tablesrdf4j.org
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­datastore/­docsrdf4j.org/­documentation
DeveloperGoogleMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release200820122004
Current release3.4, August 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedhostedLinux
OS X
Unix
Windows
Data schemeschema-freeschema-freeschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or datenoyes, details hereyesyes
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.nonono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoSQL-like query language (GQL)nono
APIs and other access methodsgRPC
JSON over HTTP
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
Server-side scripts infoStored proceduresnousing Google App Enginenoyes
Triggersyes, watching key changesCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication using Paxosyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic lockingACID 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.nonono
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights based on private key authentication or shared access signaturesno

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More resources
etcdGoogle Cloud DatastoreMicrosoft Azure Table StorageRDF4J infoformerly known as Sesame
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