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DBMS > CouchDB vs. IRONdb vs. Splice Machine vs. Tkrzw vs. VictoriaMetrics

System Properties Comparison CouchDB vs. IRONdb vs. Splice Machine vs. Tkrzw vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonIRONdb  Xexclude from comparisonSplice Machine  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelDocument storeTime Series DBMSRelational DBMSKey-value storeTime Series DBMS
Secondary database modelsSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.30
Rank#45  Overall
#7  Document stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitecouchdb.apache.orgwww.circonus.com/solutions/time-series-database/splicemachine.comdbmx.net/­tkrzwvictoriametrics.com
Technical documentationdocs.couchdb.org/­en/­stabledocs.circonus.com/irondb/category/getting-startedsplicemachine.com/­how-it-worksdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerCirconus LLC.Splice MachineMikio HirabayashiVictoriaMetrics
Initial release20052017201420202018
Current release3.3.3, December 2023V0.10.20, January 20183.1, March 20210.9.3, August 2020v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoApache version 2commercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache Version 2.0Open Source infoApache Version 2.0
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.
Implementation languageErlangC and C++JavaC++Go
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
LinuxLinux
OS X
Solaris
Windows
Linux
macOS
FreeBSD
Linux
macOS
OpenBSD
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyes infotext, numeric, histogramsyesno
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.nononono
Secondary indexesyes infovia viewsnoyes
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)yesnono
APIs and other access methodsRESTful HTTP/JSON APIHTTP APIJDBC
Native Spark Datasource
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresView functions in JavaScriptyes, in Luayes infoJavanono
Triggersyesnoyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0Automatic, metric affinity per nodeShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
configurable replication factor, datacenter awareMulti-source replication
Source-replica replication
noneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoYes, via Full Spark Integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possiblenoACIDno
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyes, multi-version concurrency control (MVCC)yesyes
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.nonoyesyes infousing specific database classesno
User concepts infoAccess controlAccess rights for users can be defined per databasenoAccess rights for users, groups and roles according to SQL-standardno

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