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DBMS > ClickHouse vs. GraphDB vs. Kinetica vs. Vertica

System Properties Comparison ClickHouse vs. GraphDB vs. Kinetica vs. Vertica

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Editorial information provided by DB-Engines
NameClickHouse  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonKinetica  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionColumn-oriented Relational DBMS powering YandexEnterprise RDF and graph database with efficient reasoning, cluster and external index synchronization supportGPU-accelerated database for real-time analysis of large and streaming datasetsColumnar relational DBMS designed to handle modern analytic workloads, enabling fast query performance
Primary database modelRelational DBMSGraph DBMS
RDF store
Relational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.31
Rank#65  Overall
#34  Relational DBMS
Score1.32
Rank#144  Overall
#10  Graph DBMS
#5  RDF stores
Score0.67
Rank#196  Overall
#94  Relational DBMS
Score20.95
Rank#31  Overall
#18  Relational DBMS
Websiteclickhouse.techgraphdb.ontotext.comwww.kinetica.comwww.vertica.com
Technical documentationclickhouse.tech/­docsgraphdb.ontotext.com/­documentationwww.kinetica.com/­docswww.vertica.com/­docs/­10.0.x/­HTML/­Content/­Home.htm
DeveloperYandex LLCOntotextKineticaVertica / Micro Focus infoprior to that Hewlett Packard
Initial release2016200020122005
Current releasev20.3.8.53, April 20208.8, January 20196.0Vertica 10.0 Software, May 2020
Vertica for SQL on Hadoop 10.0 Software, May 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infolimited edition freecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenono infoNamed S4, Ontotext provides a semantic graph database based on GraphDB in the cloud.nono infoAvailable on all major clouds - Amazon AWS, Microsoft Azure and Google Cloud Platform
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC, C++
Server operating systemsFreeBSD
Linux
macOS
All OS with a Java VM
Linux
OS X
Windows
LinuxLinux
Data schemeyesschema-free and OWL/RDFS-schema supportyesyes infoUnstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononoyes
Secondary indexesnoyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesyesno infoThe concept of 'projections' can be used instead of indexes.
SQL infoSupport of SQLClose to ANSI SQLSPARQL is used as query languageSQL-like DML and DDL statementsyes infonearly full SQL99 without support for indexes and triggers
APIs and other access methodsHTTP REST
JDBC
ODBC
Proprietary protocol
GeoSPARQL
Java API
RDF4J API
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
Kafka
ODBC
Proprietary protocol
RESTful HTTP API
Supported programming languagesC# info3rd party library
C++
Elixir info3rd party library
Go info3rd party library
Java info3rd party library
JavaScript (Node.js) info3rd party library
Kotlin info3rd party library
Nim info3rd party library
Perl info3rd party library
PHP info3rd party library
Python info3rd party library
R info3rd party library
Ruby info3rd party library
Scala info3rd party library
.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
C++
Java
Perl
Python
R
Server-side scripts infoStored proceduresnoJava Server Pluginuser defined functionsyes
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoSegmentation, Projection Segmentation, Hash Segmentation
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-master replicationMaster-slave replicationMaster-master replication infoCluster level and Object level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infowith Vertica Connector for Hadoop
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyes infoConstraint checkingyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
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.yesyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users and rolesyesAccess rights for users and roles on table levelfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
ClickHouseGraphDB infoformer name: OWLIMKineticaVertica infoVertica Analytics Platform
Specific characteristicsGraphDB Enterprise is a high-performance semantic repository created by Ontotext....
» more
Columnar storage, MPP, Hybrid storage model, Aggressive data compression, High availability,...
» more
Competitive advantagesGraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more
Performance at exabyte scale, Deploy anywhere, Open source innovation, Analysis in...
» more
Typical application scenariosMetadata enrichment and management, linked open data publishing, semantic inferencing...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersBBC, Press Association, Financial Times, DK, Euromoney, The British Museum, Getty...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsGraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more
Licensing and pricing modelsGraphDB-Free is free to use. SE and Enterprise are licensed per CPU-Core used. Perpetual...
» more
Cost-based models and subscription-based models are available
» more
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We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources
ClickHouseGraphDB infoformer name: OWLIMKineticaVertica infoVertica Analytics Platform
Conferences and events

GraphDB Fundamentals: Adding Meaning to Your Data
Webinar, 4pm GMT, 8am PST, 5pm CET, 25 March 2020 (finished)

GraphDB 9.2 Supports RDF* to Match the Expressivity of Property Graphs
Webinar, 5 pm CEST / 12 pm EDT / 6 pm EEST, 14 May 2020 (finished)

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provided by Google News

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Ontotext GraphDB Named Innovator in Bloor's Graph Database Market Research
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GPU Database Market 2020 Forecast to 2026 (Based on 2020 COVID-19 Worldwide Spread), Key Players – Graphistry, BlazingDB, Kinetica, SQream, Zilliz, etc.
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Complicated and competitive: How Vertica navigates today's intricate world of database management
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