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DBMS > Apache IoTDB vs. DataFS vs. GBase vs. QuestDB vs. Sphinx

System Properties Comparison Apache IoTDB vs. DataFS vs. GBase vs. QuestDB vs. Sphinx

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDataFS  Xexclude from comparisonGBase  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  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 FlinkAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.A high performance open source SQL database for time series dataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSObject oriented DBMSRelational DBMSTime Series DBMSSearch engine
Secondary database modelsGraph DBMSRelational 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#360  Overall
#17  Object oriented DBMS
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websiteiotdb.apache.orgnewdatabase.comwww.gbase.cnquestdb.iosphinxsearch.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldev.mobiland.com/­Overview.xspquestdb.io/­docssphinxsearch.com/­docs
DeveloperApache Software FoundationMobiland AGGeneral Data Technology Co., Ltd.QuestDB Technology IncSphinx Technologies Inc.
Initial release20182018200420142001
Current release1.1.0, April 20231.1.263, October 2022GBase 8a, GBase 8s, GBase 8c3.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
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 languageJavaC, Java, PythonJava (Zero-GC), C++, RustC++
Server operating systemsAll OS with a Java VM (>= 1.8)WindowsLinuxLinux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)yesyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nonoyesno
Secondary indexesyesnoyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languagenoStandard with numerous extensionsSQL with time-series extensionsSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
Native API
.NET Client API
Proprietary client DLL
WinRT client
ADO.NET
C API
JDBC
ODBC
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C#
C++
VB.Net
C#C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesuser defined functionsnono
Triggersyesno, except callback-events from server when changes happenedyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Proprietary Sharding systemhorizontal partitioning (by range, list and hash) and vertical partitioninghorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesSource-replica replication with eventual consistencynone
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
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infothrough memory mapped files
User concepts infoAccess controlyesWindows-Profileyesno
More information provided by the system vendor
Apache IoTDBDataFSGBaseQuestDBSphinx
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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More resources
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