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DBMS > etcd vs. Google Cloud Datastore vs. RDF4J vs. Stardog

System Properties Comparison etcd vs. Google Cloud Datastore vs. RDF4J vs. Stardog

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionA distributed reliable key-value storeAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelKey-value storeDocument storeRDF storeGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.03
Rank#54  Overall
#5  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.74
Rank#222  Overall
#9  RDF stores
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Websiteetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­datastorerdf4j.orgwww.stardog.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­datastore/­docsrdf4j.org/­documentationdocs.stardog.com
DeveloperGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Stardog-Union
Initial release200820042010
Current release3.4, August 20197.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaJava
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedLinux
OS X
Unix
Windows
Linux
macOS
Windows
Data schemeschema-freeschema-freeyes infoRDF Schemasschema-free and OWL/RDFS-schema support
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 infoImport/export of XML data possible
Secondary indexesnoyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnoSQL-like query language (GQL)noYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsgRPC
JSON over HTTP
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
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
Java
PHP
Python
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnousing Google App Engineyesuser defined functions and aggregates, HTTP Server extensions in Java
Triggersyes, watching key changesCallbacks using the Google Apps Engineyesyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingnonenone
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 PaxosnoneMulti-source replication in HA-Cluster
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 in HA-Cluster
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users and roles

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More resources
etcdGoogle Cloud DatastoreRDF4J infoformerly known as SesameStardog
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