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DBMS > Apache IoTDB vs. Atos Standard Common Repository vs. Faircom EDGE vs. Solr

System Properties Comparison Apache IoTDB vs. Atos Standard Common Repository vs. Faircom EDGE vs. Solr

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonSolr  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 networksFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelTime Series DBMSDocument store
Key-value store
Key-value store
Relational DBMS
Search engine
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
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websiteiotdb.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.faircom.com/­products/­faircom-edgesolr.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlsolr.apache.org/­resources.html
DeveloperApache Software FoundationAtos Convergence CreatorsFairCom CorporationApache Software Foundation
Initial release2018201619792006
Current release1.1.0, April 20231703V3, October 20209.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infoRestricted, free version availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaANSI C, C++Java
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxAndroid
Linux infoARM, x86
Raspbian
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)yes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesoptionalyes, ANSI Standard SQL Typesyes infosupports customizable data types and automatic 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.noyesyesyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenoyes infoANSI SQL queriesSolr Parallel SQL Interface
APIs and other access methodsJDBC
Native API
LDAPADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages with LDAP bindingsC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesnoyes info.Net, JavaScript, C/C++Java plugins
Triggersyesyesyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infocell divisionFile partitioning infoCustomizable business rules for partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesyes infoSynchronous and asynchronous realtime replication based on transaction logsyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integritynonoyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyes
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.yesyesyesyes
User concepts infoAccess controlyesLDAP bind authenticationFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.yes

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More resources
Apache IoTDBAtos Standard Common RepositoryFaircom EDGE infoformerly c-treeEDGESolr
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