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DBMS > Apache IoTDB vs. Faircom EDGE vs. HBase vs. PostgreSQL

System Properties Comparison Apache IoTDB vs. Faircom EDGE vs. HBase vs. PostgreSQL

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHBase  Xexclude from comparisonPostgreSQL  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 FlinkFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsWide-column store based on Apache Hadoop and on concepts of BigTableWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Wide column storeRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websiteiotdb.apache.orgwww.faircom.com/­products/­faircom-edgehbase.apache.orgwww.postgresql.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlhbase.apache.org/­book.htmlwww.postgresql.org/­docs
DeveloperApache Software FoundationFairCom CorporationApache Software Foundation infoApache top-level project, originally developed by PowersetPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2018197920081989 info1989: Postgres, 1996: PostgreSQL
Current release1.1.0, April 2023V3, October 20202.3.4, January 202116.2, February 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoApache version 2Open Source infoBSD
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++JavaC
Server operating systemsAll OS with a Java VM (>= 1.8)Android
Linux infoARM, x86
Raspbian
Windows
Linux
Unix
Windows infousing Cygwin
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesoptions to bring your own types, AVROyes
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.noyesnoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query languageyes infoANSI SQL queriesnoyes infostandard with numerous extensions
APIs and other access methodsJDBC
Native API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyesyes info.Net, JavaScript, C/C++yes infoCoprocessors in Javauser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersyesyesyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)File partitioning infoCustomizable business rules for partitioningShardingpartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replication
Source-replica replication
Source-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Tunable Consistency
Immediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDSingle row ACID (across millions of columns)ACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes
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.yesyesyesno
User concepts infoAccess controlyesFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standard

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Apache IoTDBFaircom EDGE infoformerly c-treeEDGEHBasePostgreSQL
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