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DBMS > Apache IoTDB vs. RDFox vs. Tigris vs. TimescaleDB

System Properties Comparison Apache IoTDB vs. RDFox vs. Tigris vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonRDFox  Xexclude from comparisonTigris  Xexclude from comparisonTimescaleDB  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 FlinkHigh performance knowledge graph and semantic reasoning engineA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructureA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSGraph DBMS
RDF store
Document store
Key-value store
Search engine
Time Series DBMS
Time Series DBMS
Secondary database modelsRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.22
Rank#305  Overall
#25  Graph DBMS
#15  RDF stores
Score0.05
Rank#359  Overall
#50  Document stores
#52  Key-value stores
#23  Search engines
#37  Time Series DBMS
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Websiteiotdb.apache.orgwww.oxfordsemantic.techwww.tigrisdata.comwww.timescale.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.oxfordsemantic.techwww.tigrisdata.com/­docsdocs.timescale.com
DeveloperApache Software FoundationOxford Semantic TechnologiesTigris Data, Inc.Timescale
Initial release2018201720222017
Current release1.1.0, April 20236.0, Septermber 20222.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
macOS
Windows
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyesyes infoRDF schemasyesyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data 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 indexesyesyesyes
SQL infoSupport of SQLSQL-like query languagenonoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
Native API
RESTful HTTP API
SPARQL 1.1
CLI Client
gRPC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
Java
Go
Java
JavaScript (Node.js)
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasreplication via a shared file systemyesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setupsImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes, using FoundationDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlyesRoles, resources, and access typesAccess rights for users and rolesfine grained access rights according to SQL-standard

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More resources
Apache IoTDBRDFoxTigrisTimescaleDB
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