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DBMS > Apache IoTDB vs. Dragonfly vs. TimescaleDB vs. Valentina Server

System Properties Comparison Apache IoTDB vs. Dragonfly vs. TimescaleDB vs. Valentina Server

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDragonfly  Xexclude from comparisonTimescaleDB  Xexclude from comparisonValentina Server  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 FlinkA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLObject-relational database and reports server
Primary database modelTime Series DBMSKey-value storeTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.44
Rank#255  Overall
#38  Key-value stores
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Score0.18
Rank#313  Overall
#140  Relational DBMS
Websiteiotdb.apache.orggithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.timescale.comwww.valentina-db.net
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.dragonflydb.io/­docsdocs.timescale.comvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperApache Software FoundationDragonflyDB team and community contributorsTimescaleParadigma Software
Initial release2018202320171999
Current release1.1.0, April 20231.0, March 20232.15.0, May 20245.7.5
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSL 1.1Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesscheme-freeyesyes
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysnumerics, 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.nonoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query languagenoyes infofull PostgreSQL SQL syntaxyes
APIs and other access methodsJDBC
Native API
Proprietary protocol infoRESP - REdis Serialization ProtocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresyesLuauser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes
Triggersyespublish/subscribe channels provide some trigger functionalityyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)yes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of command blocks and scriptsACID
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryes
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.yesyesnoyes
User concepts infoAccess controlyesPassword-based authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache IoTDBDragonflyTimescaleDBValentina Server
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