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DBMS > Apache IoTDB vs. DataFS vs. etcd vs. H2 vs. SWC-DB

System Properties Comparison Apache IoTDB vs. DataFS vs. etcd vs. H2 vs. SWC-DB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDataFS  Xexclude from comparisonetcd  Xexclude from comparisonH2  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
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 FlinkAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.A distributed reliable key-value storeFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.A high performance, scalable Wide Column DBMS
Primary database modelTime Series DBMSObject oriented DBMSKey-value storeRelational DBMSWide column store
Secondary database modelsGraph DBMSSpatial DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.09
Rank#360  Overall
#17  Object oriented DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Score8.33
Rank#46  Overall
#30  Relational DBMS
Score0.08
Rank#364  Overall
#13  Wide column stores
Websiteiotdb.apache.orgnewdatabase.cometcd.io
github.com/­etcd-io/­etcd
www.h2database.comgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldev.mobiland.com/­Overview.xspetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.h2database.com/­html/­main.html
DeveloperApache Software FoundationMobiland AGThomas MuellerAlex Kashirin
Initial release2018201820052020
Current release1.1.0, April 20231.1.263, October 20223.4, August 20192.2.220, July 20230.5, April 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0Open Source infodual-licence (Mozilla public license, Eclipse public license)Open Source infoGPL V3
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 languageJavaGoJavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)WindowsFreeBSD
Linux
Windows infoexperimental
All OS with a Java VMLinux
Data schemeyesClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesnoyes
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.nonononono
Secondary indexesyesnonoyes
SQL infoSupport of SQLSQL-like query languagenonoyesSQL-like query language
APIs and other access methodsJDBC
Native API
.NET Client API
Proprietary client DLL
WinRT client
gRPC
JSON over HTTP
JDBC
ODBC
Proprietary protocol
Thrift
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C#
C++
VB.Net
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
JavaC++
Server-side scripts infoStored proceduresyesnoJava Stored Procedures and User-Defined Functionsno
Triggersyesno, except callback-events from server when changes happenedyes, watching key changesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Proprietary Sharding systemnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.With clustering: 2 database servers on different computers operate on identical copies of a database
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
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.yesnonoyesno
User concepts infoAccess controlyesWindows-Profilenofine grained access rights according to SQL-standard

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More resources
Apache IoTDBDataFSetcdH2SWC-DB infoSuper Wide Column Database
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