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

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

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA 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.
Primary database modelRelational DBMSKey-value storeDocument storeRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
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
Websitewww.datomic.cometcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­datastorerdf4j.org
Technical documentationdocs.datomic.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­datastore/­docsrdf4j.org/­documentation
DeveloperCognitectGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release201220082004
Current release1.0.6735, June 20233.4, August 2019
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2.0commercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureGoJava
Server operating systemsAll OS with a Java VMFreeBSD
Linux
Windows infoexperimental
hostedLinux
OS X
Unix
Windows
Data schemeyesschema-freeschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesnoyes, details hereyes
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 indexesyesnoyesyes
SQL infoSupport of SQLnonoSQL-like query language (GQL)no
APIs and other access methodsRESTful HTTP APIgRPC
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
Supported programming languagesClojure
Java
.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
Server-side scripts infoStored proceduresyes infoTransaction Functionsnousing Google App Engineyes
TriggersBy using transaction functionsyes, watching key changesCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes 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.yes inforecommended only for testing and developmentnono
User concepts infoAccess controlnonoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
DatomicetcdGoogle Cloud DatastoreRDF4J infoformerly known as Sesame
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