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DBMS > ArangoDB vs. ClickHouse vs. GraphDB vs. GridGain vs. Kinetica

System Properties Comparison ArangoDB vs. ClickHouse vs. GraphDB vs. GridGain vs. Kinetica

Editorial information provided by DB-Engines
NameArangoDB  Xexclude from comparisonClickHouse  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonGridGain  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionNative multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.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.GridGain is an in-memory computing platform, built on Apache IgniteFully vectorized database across both GPUs and CPUs
Primary database modelDocument store
Graph DBMS
Key-value store
Search engine
Relational DBMSGraph DBMS
RDF store
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsTime Series DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.32
Rank#90  Overall
#15  Document stores
#5  Graph DBMS
#12  Key-value stores
#10  Search engines
Score16.34
Rank#38  Overall
#23  Relational DBMS
Score3.32
Rank#91  Overall
#6  Graph DBMS
#4  RDF stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitearangodb.comclickhouse.comwww.ontotext.comwww.gridgain.comwww.kinetica.com
Technical documentationdocs.arangodb.comclickhouse.com/­docsgraphdb.ontotext.com/­documentationwww.gridgain.com/­docs/­index.htmldocs.kinetica.com
Social network pagesLinkedInTwitterYouTubeFacebookInstagramLinkedInTwitterYouTubeGitHubMedium
DeveloperArangoDB Inc.Clickhouse Inc.OntotextGridGain Systems, Inc.Kinetica
Initial release20122016200020072012
Current release3.11.5, November 2023v24.4.1.2088-stable, May 202410.4, October 2023GridGain 8.5.17.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial license (Enterprise) availableOpen Source infoApache 2.0commercial infoSome plugins of GraphDB Workbench are open sourcedcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
ArangoDB Cloud –The Managed Cloud Service of ArangoDB. Provides fully managed, and monitored cluster deployments of any size, with enterprise-grade security. Get started for free and continue for as little as $0,21/hour.
  • DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
  • ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
  • Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
Implementation languageC++C++JavaJava, C++, .NetC, C++
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
macOS
All OS with a Java VM
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-free infoautomatically recognizes schema within a collectionyesschema-free and OWL/RDFS-schema support; RDF shapesyesyes
Typing infopredefined data types such as float or dateyes infostring, double, boolean, list, hashyesyesyesyes
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.nonoyesno
Secondary indexesyesyesyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesyesyes
SQL infoSupport of SQLnoClose to ANSI SQL (SQL/JSON + extensions)stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statements
APIs and other access methodsAQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream
gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol
GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust
C# 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
Rust
Scala info3rd party library
.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresJavaScriptyeswell-defined plugin interfaces; JavaScript server-side extensibilityyes (compute grid and cache interceptors can be used instead)user defined functions
Triggersnononoyes (cache interceptors and events)yes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesSharding infosince version 2.0key based and customnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication with configurable replication factorAsynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.Multi-source replicationyes (replicated cache)Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infocan be done with stored procedures in JavaScriptnonoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoconfigurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)
Immediate ConsistencyImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes inforelationships in graphsnoyes infoConstraint checkingnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlyesAccess rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.Default 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.Security Hooks for custom implementationsAccess rights for users and roles on table level
More information provided by the system vendor
ArangoDBClickHouseGraphDB infoformer name: OWLIMGridGainKinetica
Specific characteristicsGraph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
» more
Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more
Competitive advantagesConsolidation: As a native multi-model database, can be used as a full blown document...
» more
GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more
Typical application scenariosNative multi-model in ArangoDB is being used for a broad range of projects across...
» more
Metadata enrichment and management, linked data publishing, semantic inferencing...
» more
Key customersCisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
» more
​ GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more
Market metricsArangoDB is the leading native multi-model database with over 11,000 stargazers on...
» more
GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more
Licensing and pricing modelsVery permissive Apache 2 License for Community Edition & commercial licenses are...
» more
GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more
News

Integrating GraphDB with Relational Database Systems
23 May 2024

Understanding the Graph Center of Excellence
17 May 2024

Migrating From LPG to RDF Graph Model
8 May 2024

Case study: Policy Enforcement Automation With Semantics
2 May 2024

Okay, RAG… We Have a Problem
26 April 2024

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
3rd partiesDoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
» more

Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
» more

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
ArangoDBClickHouseGraphDB infoformer name: OWLIMGridGainKinetica
DB-Engines blog posts

The Weight of Relational Databases: Time for Multi-Model?
29 August 2017, Luca Olivari (guest author)

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Recent citations in the news

ArangoGraphML: Simplifying the Power of Graph Machine Learning
11 October 2023, Datanami

How to Build Knowledge Graph Enhanced Chatbot with ChatGPT and ArangoDB
30 June 2023, DataDrivenInvestor

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30 May 2023, insideHPC

ArangoDB brings yet more money into graph database market with $27.8M round
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Ontotext's GraphDB Solution is Now Available on the Microsoft Azure Marketplace
16 January 2024, PR Newswire

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Ontotext Platform 3.0 for Enterprise Knowledge Graphs Released
18 December 2019, KDnuggets

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15 January 2020, The Register

Ontotext's GraphDB 8.10 Makes Knowledge Graph Experience Faster and Richer
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GridGain's 2023 Growth Positions Company for Strong 2024
25 January 2024, Datanami

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Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Kinetica Delivers Real-Time Vector Similarity Search
22 March 2024, Geospatial World

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