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DBMS > ArangoDB vs. CockroachDB vs. QuestDB

System Properties Comparison ArangoDB vs. CockroachDB vs. QuestDB

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Editorial information provided by DB-Engines
NameArangoDB  Xexclude from comparisonCockroachDB  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionNative multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.A high performance open source SQL database for time series data
Primary database modelDocument store
Graph DBMS
Key-value store
Search engine
Relational DBMSTime Series DBMS
Secondary database modelsRelational 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
Score6.15
Rank#55  Overall
#33  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Websitearangodb.comwww.cockroachlabs.comquestdb.io
Technical documentationdocs.arangodb.comwww.cockroachlabs.com/­docsquestdb.io/­docs
Social network pagesLinkedInTwitterFacebookYouTubeInstagram
DeveloperArangoDB Inc.Cockroach LabsQuestDB Technology Inc
Initial release201220152014
Current release3.11.5, November 202323.1.1, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial license (Enterprise) availableOpen Source infoApache 2.0, commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
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.
Implementation languageC++GoJava (Zero-GC), C++, Rust
Server operating systemsLinux
OS X
Windows
Linux
macOS
Windows
Linux
macOS
Windows
Data schemeschema-free infoautomatically recognizes schema within a collectiondynamic schemayes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyes infostring, double, boolean, list, hashyesyes
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.nono
Secondary indexesyesyesno
SQL infoSupport of SQLnoyes, wire compatible with PostgreSQLSQL with time-series extensions
APIs and other access methodsAQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream
JDBCHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesC#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresJavaScriptnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infosince version 2.0horizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFThorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication with configurable replication factorMulti-source replication using RAFTSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infocan be done with stored procedures in JavaScriptnono
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
Foreign keys infoReferential integrityyes inforelationships in graphsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infothrough memory mapped files
User concepts infoAccess controlyesRole-based access control
More information provided by the system vendor
ArangoDBCockroachDBQuestDB
Specific characteristicsGraph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
» more
Relational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesConsolidation: As a native multi-model database, can be used as a full blown document...
» more
High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosNative multi-model in ArangoDB is being used for a broad range of projects across...
» more
Financial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersCisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
» more
Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Market metricsArangoDB is the leading native multi-model database with over 11,000 stargazers on...
» more
Licensing and pricing modelsVery permissive Apache 2 License for Community Edition & commercial licenses are...
» more
Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
ArangoDBCockroachDBQuestDB
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

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