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DBMS > Apache IoTDB vs. IRONdb vs. Kdb vs. Sqrrl

System Properties Comparison Apache IoTDB vs. IRONdb vs. Kdb vs. Sqrrl

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonIRONdb  Xexclude from comparisonKdb  Xexclude from comparisonSqrrl  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityHigh performance Time Series DBMSAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelTime Series DBMSTime Series DBMSTime Series DBMS
Vector DBMS
Document store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Websiteiotdb.apache.orgwww.circonus.com/solutions/time-series-database/kx.comsqrrl.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.circonus.com/irondb/category/getting-startedcode.kx.com
DeveloperApache Software FoundationCirconus LLC.Kx Systems, a division of First Derivatives plcAmazon infooriginally Sqrrl Data, Inc.
Initial release201820172000 infokdb was released 2000, kdb+ in 20032012
Current release1.1.0, April 2023V0.10.20, January 20183.6, May 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree 32-bit versioncommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++qJava
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
OS X
Solaris
Windows
Linux
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesyes
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.nonoyes
Secondary indexesyesnoyes infotable attribute 'grouped'yes
SQL infoSupport of SQLSQL-like query languageSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like query language (q)no
APIs and other access methodsJDBC
Native API
HTTP APIHTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyesyes, in Luauser defined functionsno
Triggersyesnoyes infowith viewsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Automatic, metric affinity per nodehorizontal partitioningSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasconfigurable replication factor, datacenter awareSource-replica replicationselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknono infosimilar paradigm used for internal processingyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate consistency per node, eventual consistency across nodesImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoAtomic updates per row, document, or graph entity
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.yesnoyes
User concepts infoAccess controlyesnorights management via user accountsCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)
More information provided by the system vendor
Apache IoTDBIRONdbKdbSqrrl
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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Apache IoTDBIRONdbKdbSqrrl
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