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DBMS > Apache IoTDB vs. Faircom EDGE vs. Graph Engine vs. HBase vs. QuestDB

System Properties Comparison Apache IoTDB vs. Faircom EDGE vs. Graph Engine vs. HBase vs. QuestDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHBase  Xexclude from comparisonQuestDB  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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineWide-column store based on Apache Hadoop and on concepts of BigTableA high performance open source SQL database for time series data
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Graph DBMS
Key-value store
Wide column storeTime Series DBMS
Secondary database modelsRelational DBMS
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
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Websiteiotdb.apache.orgwww.faircom.com/­products/­faircom-edgewww.graphengine.iohbase.apache.orgquestdb.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlwww.graphengine.io/­docs/­manualhbase.apache.org/­book.htmlquestdb.io/­docs
DeveloperApache Software FoundationFairCom CorporationMicrosoftApache Software Foundation infoApache top-level project, originally developed by PowersetQuestDB Technology Inc
Initial release20181979201020082014
Current release1.1.0, April 2023V3, October 20202.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoMIT LicenseOpen Source infoApache version 2Open Source infoApache 2.0
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++.NET and CJavaJava (Zero-GC), C++, Rust
Server operating systemsAll OS with a Java VM (>= 1.8)Android
Linux infoARM, x86
Raspbian
Windows
.NETLinux
Unix
Windows infousing Cygwin
Linux
macOS
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesschema-free, schema definition possibleyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesoptions to bring your own types, AVROyes
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.noyesnonono
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL-like query languageyes infoANSI SQL queriesnonoSQL with time-series extensions
APIs and other access methodsJDBC
Native API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
RESTful HTTP APIJava API
RESTful HTTP API
Thrift
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
C++
F#
Visual Basic
C
C#
C++
Groovy
Java
PHP
Python
Scala
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresyesyes info.Net, JavaScript, C/C++yesyes infoCoprocessors in Javano
Triggersyesyesnoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)File partitioning infoCustomizable business rules for partitioninghorizontal partitioningShardinghorizontal partitioning (by timestamps)
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
Source-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Tunable Consistency
Immediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoSingle row ACID (across millions of columns)ACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyesyes infothrough memory mapped files
User concepts infoAccess controlyesFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC
More information provided by the system vendor
Apache IoTDBFaircom EDGE infoformerly c-treeEDGEGraph Engine infoformer name: TrinityHBaseQuestDB
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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