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DBMS > CouchDB vs. GridDB vs. SQL.JS vs. TimescaleDB vs. Vertica

System Properties Comparison CouchDB vs. GridDB vs. SQL.JS vs. TimescaleDB vs. Vertica

Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonGridDB  Xexclude from comparisonSQL.JS  Xexclude from comparisonTimescaleDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Scalable in-memory time series database optimized for IoT and Big DataPort of SQLite to JavaScriptA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelDocument storeTime Series DBMSRelational DBMSTime Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS infousing the Geocouch extensionKey-value store
Relational DBMS
Relational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.30
Rank#47  Overall
#7  Document stores
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.63
Rank#241  Overall
#112  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitecouchdb.apache.orggriddb.netsql.js.orgwww.timescale.comwww.vertica.com
Technical documentationdocs.couchdb.org/­en/­stabledocs.griddb.netsql.js.org/­documentation/­index.htmldocs.timescale.comvertica.com/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerToshiba CorporationAlon Zakai infoenhancements implemented by othersTimescaleOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20052013201220172005
Current release3.3.3, December 20235.1, August 20222.15.0, May 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache version 2Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen SourceOpen Source infoApache 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC++JavaScriptCC++
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
Linuxserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
Linux
Data schemeschema-freeyesyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or datenoyes infonumerical, string, blob, geometry, boolean, timestampyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.nononoyesno
Secondary indexesyes infovia viewsyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)yes infoSQL-92 is not fully supportedyes infofull PostgreSQL SQL syntaxFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP/JSON APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JavaScript APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
JavaScript.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresView functions in JavaScriptnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyesnoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0Shardingnoneyes, across time and space (hash partitioning) attributeshorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationnoneSource-replica replication with hot standby and reads on replicas infoMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containersnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possibleACID at container levelACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyesyes
Durability infoSupport for making data persistentyesyesno infoexcept by serializing a db to a fileyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesnono
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights for users can be defined per databasenofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"GridDBSQL.JSTimescaleDBVertica infoOpenText™ Vertica™
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"GridDBSQL.JSTimescaleDBVertica infoOpenText™ Vertica™
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