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DBMS > Apache IoTDB vs. ReductStore

System Properties Comparison Apache IoTDB vs. ReductStore

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonReductStore  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 FlinkDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.
Primary database modelTime Series DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.39
Rank#155  Overall
#14  Time Series DBMS
Score0.00
Rank#388  Overall
#40  Time Series DBMS
Websiteiotdb.apache.orggithub.com/­reductstore
www.reduct.store
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.reduct.store/­docs
DeveloperApache Software FoundationReductStore LLC
Initial release20182023
Current release1.1.0, April 20231.9, March 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBusiness Source License 1.1
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Rust
Server operating systemsAll OS with a Java VM (>= 1.8)Docker
Linux
macOS
Windows
Data schemeyes
Typing infopredefined data types such as float or dateyes
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.no
Secondary indexesyes
SQL infoSupport of SQLSQL-like query language
APIs and other access methodsJDBC
Native API
HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C++
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresyes
Triggersyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano
Concurrency infoSupport for concurrent manipulation of datayes
Durability infoSupport for making data persistentyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlyes

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More resources
Apache IoTDBReductStore
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