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DBMS > Apache IoTDB vs. BigObject vs. Faircom EDGE vs. Splice Machine

System Properties Comparison Apache IoTDB vs. BigObject vs. Faircom EDGE vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBigObject  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonSplice Machine  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 FlinkAnalytic DBMS for real-time computations and queriesFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSRelational DBMS infoa hierachical model (tree) can be imposedKey-value store
Relational 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
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteiotdb.apache.orgbigobject.iowww.faircom.com/­products/­faircom-edgesplicemachine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.bigobject.iodocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlsplicemachine.com/­how-it-works
DeveloperApache Software FoundationBigObject, Inc.FairCom CorporationSplice Machine
Initial release2018201519792014
Current release1.1.0, April 2023V3, October 20203.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availablecommercial infoRestricted, free version availableOpen Source infoAGPL 3.0, commercial license available
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++Java
Server operating systemsAll OS with a Java VM (>= 1.8)Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Android
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Solaris
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.nonoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsyes infoANSI SQL queriesyes
APIs and other access methodsJDBC
Native API
fluentd
ODBC
RESTful HTTP API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesLuayes info.Net, JavaScript, C/C++yes infoJava
Triggersyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneFile partitioning infoCustomizable business rules for partitioningShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnoneyes infoSynchronous and asynchronous realtime replication based on transaction logsMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
noneImmediate Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesyes infowhen using SQLyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yes infoacross SQL and NoSQLyes, multi-version concurrency control (MVCC)
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 controlyesnoFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access rights for users, groups and roles according to SQL-standard

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More resources
Apache IoTDBBigObjectFaircom EDGE infoformerly c-treeEDGESplice Machine
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