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DBMS > Apache IoTDB vs. Faircom DB vs. GridDB vs. QuestDB

System Properties Comparison Apache IoTDB vs. Faircom DB vs. GridDB vs. QuestDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGridDB  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 FlinkNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Scalable in-memory time series database optimized for IoT and Big DataA high performance open source SQL database for time series data
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Time Series DBMSTime Series DBMS
Secondary database modelsKey-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
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Websiteiotdb.apache.orgwww.faircom.com/­products/­faircom-dbgriddb.netquestdb.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.griddb.netquestdb.io/­docs
DeveloperApache Software FoundationFairCom CorporationToshiba CorporationQuestDB Technology Inc
Initial release2018197920132014
Current release1.1.0, April 2023V12, November 20205.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaANSI C, C++C++Java (Zero-GC), C++, Rust
Server operating systemsAll OS with a Java VM (>= 1.8)AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
LinuxLinux
macOS
Windows
Data schemeyesschema free, schema optional, schema required, partial schema,yesyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyes infonumerical, string, blob, geometry, boolean, timestampyes
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query languageyes, ANSI SQL with proprietary extensionsSQL92, SQL-like TQL (Toshiba Query Language)SQL with time-series extensions
APIs and other access methodsJDBC
Native API
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresyesyes info.Net, JavaScript, C/C++nono
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)File partitioning, horizontal partitioning, sharding infoCustomizable business rules for table 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, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Source-replica replicationSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually ConsistentACID at container levelACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes infothrough memory mapped files
User concepts infoAccess controlyesFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users can be defined per database
More information provided by the system vendor
Apache IoTDBFaircom DB infoformerly c-treeACEGridDBQuestDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Relational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Financial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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