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

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

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAutomatically 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 DBMSRelational DBMSDocument storeRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.74
Rank#222  Overall
#9  RDF stores
Websitebrytlyt.iowww.datomic.comcloud.google.com/­datastorerdf4j.org
Technical documentationdocs.brytlyt.iodocs.datomic.comcloud.google.com/­datastore/­docsrdf4j.org/­documentation
DeveloperBrytlytCognitectGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2016201220082004
Current release5.0, August 20231.0.7075, December 2023
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freecommercialOpen 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 languageC, C++ and CUDAJava, ClojureJava
Server operating systemsLinux
OS X
Windows
All OS with a Java VMhostedLinux
OS X
Unix
Windows
Data schemeyesyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyesyes, 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.yes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesnoSQL-like query language (GQL)no
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP APIgRPC (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 languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Clojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLyes infoTransaction Functionsusing Google App Engineyes
TriggersyesBy using transaction functionsCallbacks 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 nodesSource-replica replicationnone infoBut extensive use of caching in the application peersMulti-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 integrityyesnoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID 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 persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes 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 developmentno
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
BrytlytDatomicGoogle Cloud DatastoreRDF4J infoformerly known as Sesame
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