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DBMS > Apache IoTDB vs. BigObject vs. Drizzle vs. Faircom EDGE

System Properties Comparison Apache IoTDB vs. BigObject vs. Drizzle vs. Faircom EDGE

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBigObject  Xexclude from comparisonDrizzle  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
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 queriesMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments
Primary database modelTime Series DBMSRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSKey-value store
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
Websiteiotdb.apache.orgbigobject.iowww.faircom.com/­products/­faircom-edge
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.bigobject.iodocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html
DeveloperApache Software FoundationBigObject, Inc.Drizzle project, originally started by Brian AkerFairCom Corporation
Initial release2018201520081979
Current release1.1.0, April 20237.2.4, September 2012V3, October 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availableOpen Source infoGNU GPLcommercial infoRestricted, free version available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++ANSI C, C++
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)
FreeBSD
Linux
OS X
Android
Linux infoARM, x86
Raspbian
Windows
Data schemeyesyesyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyesyesyes, ANSI Standard SQL Types
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 infowith proprietary extensionsyes infoANSI SQL queries
APIs and other access methodsJDBC
Native API
fluentd
ODBC
RESTful HTTP API
JDBCADO.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
C
C++
Java
PHP
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
Server-side scripts infoStored proceduresyesLuanoyes info.Net, JavaScript, C/C++
Triggersyesnono infohooks for callbacks inside the server can be used.yes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingFile partitioning infoCustomizable business rules for 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 replicasnoneMulti-source replication
Source-replica replication
yes infoSynchronous and asynchronous realtime replication based on transaction logs
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
noneImmediate Consistency
Tunable Consistency
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesyesyes infowhen using SQL
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)yesyes 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
User concepts infoAccess controlyesnoPluggable authentication mechanisms infoe.g. LDAP, HTTPFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

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More resources
Apache IoTDBBigObjectDrizzleFaircom EDGE infoformerly c-treeEDGE
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