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DBMS > Apache IoTDB vs. Faircom EDGE vs. JaguarDB vs. Spark SQL

System Properties Comparison Apache IoTDB vs. Faircom EDGE vs. JaguarDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonJaguarDB  Xexclude from comparisonSpark SQL  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 environmentsPerformant, highly scalable DBMS for AI and IoT applicationsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Key-value store
Vector DBMS
Relational 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
Score0.06
Rank#381  Overall
#59  Key-value stores
#15  Vector DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteiotdb.apache.orgwww.faircom.com/­products/­faircom-edgewww.jaguardb.comspark.apache.org/­sql
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlwww.jaguardb.com/­support.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationFairCom CorporationDataJaguar, Inc.Apache Software Foundation
Initial release2018197920152014
Current release1.1.0, April 2023V3, October 20203.3 July 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoGPL V3.0Open Source infoApache 2.0
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++C++ infothe server part. Clients available in other languagesScala
Server operating systemsAll OS with a Java VM (>= 1.8)Android
Linux infoARM, x86
Raspbian
Windows
LinuxLinux
OS X
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyes
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.noyesnono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query languageyes infoANSI SQL queriesA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersSQL-like DML and DDL statements
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
ODBC
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyes info.Net, JavaScript, C/C++nono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)File partitioning infoCustomizable business rules for partitioningShardingyes, utilizing Spark Core
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 replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
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.yesyesnono
User concepts infoAccess controlyesFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.rights management via user accountsno

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More resources
Apache IoTDBFaircom EDGE infoformerly c-treeEDGEJaguarDBSpark SQL
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