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DBMS > Brytlyt vs. Google Cloud Datastore vs. Newts vs. RDF4J vs. Sphinx

System Properties Comparison Brytlyt vs. Google Cloud Datastore vs. Newts vs. RDF4J vs. Sphinx

Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonNewts  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTime Series DBMS based on CassandraRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSDocument storeTime Series DBMSRDF storeSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#279  Overall
#126  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score0.00
Rank#396  Overall
#42  Time Series DBMS
Score0.71
Rank#231  Overall
#9  RDF stores
Score6.03
Rank#60  Overall
#6  Search engines
Websitebrytlyt.iocloud.google.com/­datastoreopennms.github.io/­newtsrdf4j.orgsphinxsearch.com
Technical documentationdocs.brytlyt.iocloud.google.com/­datastore/­docsgithub.com/­OpenNMS/­newts/­wikirdf4j.org/­documentationsphinxsearch.com/­docs
DeveloperBrytlytGoogleOpenNMS GroupSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Sphinx Technologies Inc.
Initial release20162008201420042001
Current release5.0, August 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoEclipse Distribution License (EDL), v1.0.Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ and CUDAJavaJavaC++
Server operating systemsLinux
OS X
Windows
hostedLinux
OS X
Windows
Linux
OS X
Unix
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyesno
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 indexesyesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLyesSQL-like query language (GQL)nonoSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP REST
Java API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Proprietary protocol
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaJava
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLusing Google App Enginenoyesno
TriggersyesCallbacks using the Google Apps Enginenoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandranoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using Paxosselectable replication factor infobased on Cassandranonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
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.Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nonono

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More resources
BrytlytGoogle Cloud DatastoreNewtsRDF4J infoformerly known as SesameSphinx
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