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DBMS > Apache IoTDB vs. Faircom EDGE vs. Informix vs. Microsoft Access vs. Oracle Berkeley DB

System Properties Comparison Apache IoTDB vs. Faircom EDGE vs. Informix vs. Microsoft Access vs. Oracle Berkeley DB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonInformix  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonOracle Berkeley DB  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 environmentsA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Widely used in-process key-value store
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Relational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries 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
Score17.87
Rank#35  Overall
#22  Relational DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Websiteiotdb.apache.orgwww.faircom.com/­products/­faircom-edgewww.ibm.com/­products/­informixwww.microsoft.com/­en-us/­microsoft-365/­accesswww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
developer.microsoft.com/­en-us/­accessdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperApache Software FoundationFairCom CorporationIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.MicrosoftOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release20181979198419921994
Current release1.1.0, April 2023V3, October 202014.10.FC5, November 20201902 (16.0.11328.20222), March 201918.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availablecommercial infofree developer edition availablecommercial infoBundled with Microsoft OfficeOpen Source infocommercial license available
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 languageJavaANSI C, C++C, C++ and JavaC++C, Java, C++ (depending on the Berkeley DB edition)
Server operating systemsAll OS with a Java VM (>= 1.8)Android
Linux infoARM, x86
Raspbian
Windows
AIX
HP-UX
Linux
macOS
Solaris
Windows
Windows infoNot a real database server, but making use of DLLsAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyesschema-free
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyes infoSince Version 12.10 support for JSON/BSON datatypesyesno
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.noyesyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageyes infoANSI SQL queriesyesyes infobut not compliant to any SQL standardyes infoSQL interfaced based on SQLite is available
APIs and other access methodsJDBC
Native API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresyesyes info.Net, JavaScript, C/C++yesyes infosince Access 2010 using the ACE-engineno
Triggersyesyesyesyes infosince Access 2010 using the ACE-engineyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)File partitioning infoCustomizable business rules for partitioningShardingnonenone
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
noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID infobut no files for transaction loggingACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlyesFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Users with fine-grained authentication, authorization, and auditing controlsno infoa simple user-level security was built in till version Access 2003no

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More resources
Apache IoTDBFaircom EDGE infoformerly c-treeEDGEInformixMicrosoft AccessOracle Berkeley DB
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