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DBMS > Brytlyt vs. Databricks vs. GraphDB vs. Hawkular Metrics

System Properties Comparison Brytlyt vs. Databricks vs. GraphDB vs. Hawkular Metrics

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonDatabricks  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonHawkular Metrics  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.
Primary database modelRelational DBMSDocument store
Relational DBMS
Graph DBMS
RDF store
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#292  Overall
#132  Relational DBMS
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score2.76
Rank#99  Overall
#8  Graph DBMS
#4  RDF stores
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Websitebrytlyt.iowww.databricks.comwww.ontotext.comwww.hawkular.org
Technical documentationdocs.brytlyt.iodocs.databricks.comgraphdb.ontotext.com/­documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guide
Social network pagesLinkedInTwitterYouTubeGitHubMedium
DeveloperBrytlytDatabricksOntotextCommunity supported by Red Hat
Initial release2016201320002014
Current release5.0, August 202310.4, October 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infoSome plugins of GraphDB Workbench are open sourcedOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ and CUDAJavaJava
Server operating systemsLinux
OS X
Windows
hostedAll OS with a Java VM
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-free and OWL/RDFS-schema support; RDF shapesschema-free
Typing infopredefined data types such as float or dateyesyesyes
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.yesnono
Secondary indexesyesyesyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesno
SQL infoSupport of SQLyeswith Databricks SQLstored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCno
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
HTTP REST
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Python
R
Scala
.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Go
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLuser defined functions and aggregateswell-defined plugin interfaces; JavaScript server-side extensibilityno
Triggersyesnoyes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesMulti-source replicationselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integrityyesyes infoConstraint checkingno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
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-standardDefault Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.no
More information provided by the system vendor
BrytlytDatabricksGraphDB infoformer name: OWLIMHawkular Metrics
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more
Competitive advantagesGraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more
Typical application scenariosMetadata enrichment and management, linked data publishing, semantic inferencing...
» more
Key customers​ GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more
Market metricsGraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more
Licensing and pricing modelsGraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more
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