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DBMS > Apache IoTDB vs. Bangdb vs. FoundationDB vs. VictoriaMetrics

System Properties Comparison Apache IoTDB vs. Bangdb vs. FoundationDB vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBangdb  Xexclude from comparisonFoundationDB  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the 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 FlinkConverged and high performance database for device data, events, time series, document and graphOrdered key-value store. Core features are complimented by layers.A fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelTime Series DBMSDocument store
Graph DBMS
Time Series DBMS
Document store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Time Series DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websiteiotdb.apache.orgbangdb.comgithub.com/­apple/­foundationdbvictoriametrics.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.bangdb.comapple.github.io/­foundationdbdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperApache Software FoundationSachin Sinha, BangDBFoundationDBVictoriaMetrics
Initial release2018201220132018
Current release1.1.0, April 2023BangDB 2.0, October 20216.2.28, November 2020v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSD 3Open Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++C++Go
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeyesschema-freeschema-free infosome layers support schemas
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsno infosome layers support typing
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.nonono
Secondary indexesyesyes infosecondary, composite, nested, reverse, geospatialno
SQL infoSupport of SQLSQL-like query languageSQL like support with command line toolsupported in specific SQL layer onlyno
APIs and other access methodsJDBC
Native API
Proprietary protocol
RESTful HTTP API
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
Python
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
Server-side scripts infoStored proceduresyesnoin SQL-layer onlyno
Triggersyesyes, Notifications (with Streaming only)nono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factor, Knob for CAP (enterprise version only)yesSynchronous replication
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
Tunable consistency, set CAP knob accordinglyLinearizable consistencyEventual Consistency
Foreign keys infoReferential integritynonoin SQL-layer onlyno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, run db with in-memory only modeno
User concepts infoAccess controlyesyes (enterprise version only)no

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More resources
Apache IoTDBBangdbFoundationDBVictoriaMetrics
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