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DBMS > Apache IoTDB vs. Brytlyt vs. Faircom EDGE vs. Realm

System Properties Comparison Apache IoTDB vs. Brytlyt vs. Faircom EDGE vs. Realm

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBrytlyt  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonRealm  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 FlinkScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelTime Series DBMSRelational DBMSKey-value store
Relational DBMS
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Websiteiotdb.apache.orgbrytlyt.iowww.faircom.com/­products/­faircom-edgerealm.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.brytlyt.iodocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlrealm.io/­docs
DeveloperApache Software FoundationBrytlytFairCom CorporationRealm, acquired by MongoDB in May 2019
Initial release2018201619792014
Current release1.1.0, April 20235.0, August 2023V3, October 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infoRestricted, free version availableOpen Source
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++ and CUDAANSI C, C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
Android
Linux infoARM, x86
Raspbian
Windows
Android
Backend: server-less
iOS
Windows
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyesyes, ANSI Standard SQL Typesyes
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.noyes infospecific XML-type available, but no XML query functionality.yesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageyesyes infoANSI SQL queriesno
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresyesuser defined functions infoin PL/pgSQLyes info.Net, JavaScript, C/C++no inforuns within the applications so server-side scripts are unnecessary
Triggersyesyesyesyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)File partitioning infoCustomizable business rules for partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationyes infoSynchronous and asynchronous realtime replication based on transaction logsnone
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 ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQL
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.yesyesyes infoIn-Memory realm
User concepts infoAccess controlyesfine grained access rights according to SQL-standardFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.yes

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More resources
Apache IoTDBBrytlytFaircom EDGE infoformerly c-treeEDGERealm
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