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DBMS > Apache Druid vs. Apache IoTDB vs. Faircom EDGE vs. STSdb vs. VictoriaMetrics

System Properties Comparison Apache Druid vs. Apache IoTDB vs. Faircom EDGE vs. STSdb vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache IoTDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonSTSdb  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMSKey-value store
Relational DBMS
Key-value storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitedruid.apache.orgiotdb.apache.orgwww.faircom.com/­products/­faircom-edgegithub.com/­STSSoft/­STSdb4victoriametrics.com
Technical documentationdruid.apache.org/­docs/­latest/­designiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperApache Software Foundation and contributorsApache Software FoundationFairCom CorporationSTS Soft SCVictoriaMetrics
Initial release20122018197920112018
Current release29.0.1, April 20241.1.0, April 2023V3, October 20204.0.8, September 2015v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoGPLv2, commercial license availableOpen 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 languageJavaJavaANSI C, C++C#Go
Server operating systemsLinux
OS X
Unix
All OS with a Java VM (>= 1.8)Android
Linux infoARM, x86
Raspbian
Windows
WindowsFreeBSD
Linux
macOS
OpenBSD
Data schemeyes infoschema-less columns are supportedyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyesyes, ANSI Standard SQL Typesyes infoprimitive types and user defined types (classes)
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.nonoyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL for queryingSQL-like query languageyes infoANSI SQL queriesnono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
Native API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
.NET Client APIGraphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
Java
Server-side scripts infoStored proceduresnoyesyes info.Net, JavaScript, C/C++nono
Triggersnoyesyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioning (by time range) + vertical partitioning (by deviceId)File partitioning infoCustomizable business rules for partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infoSynchronous and asynchronous realtime replication based on transaction logsnoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integritynonoyes infowhen using SQLnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyesyes
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.noyesyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.no

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More resources
Apache DruidApache IoTDBFaircom EDGE infoformerly c-treeEDGESTSdbVictoriaMetrics
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