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DBMS > Apache IoTDB vs. Atos Standard Common Repository vs. NSDb vs. OrigoDB vs. VictoriaMetrics

System Properties Comparison Apache IoTDB vs. Atos Standard Common Repository vs. NSDb vs. OrigoDB vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonNSDb  Xexclude from comparisonOrigoDB  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
This system has been discontinued and will be 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 FlinkHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesA fully ACID in-memory object graph databaseA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelTime Series DBMSDocument store
Key-value store
Time Series DBMSDocument store
Object oriented DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websiteiotdb.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorynsdb.ioorigodb.comvictoriametrics.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlnsdb.io/­Architectureorigodb.com/­docsdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperApache Software FoundationAtos Convergence CreatorsRobert Friberg et alVictoriaMetrics
Initial release2018201620172009 infounder the name LiveDB2018
Current release1.1.0, April 20231703v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0Open SourceOpen Source infoApache Version 2.0
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 languageJavaJavaJava, ScalaC#Go
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
macOS
Linux
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeyesSchema and schema-less with LDAP viewsyes
Typing infopredefined data types such as float or dateyesoptionalyes: int, bigint, decimal, stringUser defined using .NET types and collections
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.noyesnono infocan be achieved using .NETno
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like query languagenono
APIs and other access methodsJDBC
Native API
LDAPgRPC
HTTP REST
WebSocket
.NET Client API
HTTP API
LINQ
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages with LDAP bindingsJava
Scala
.Net
Server-side scripts infoStored proceduresyesnonoyesno
Triggersyesyesyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infocell divisionShardinghorizontal partitioning infoclient side managed; servers are not synchronized
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesSource-replica replicationSynchronous 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
Immediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlyesLDAP bind authenticationRole based authorization

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More resources
Apache IoTDBAtos Standard Common RepositoryNSDbOrigoDBVictoriaMetrics
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