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DBMS > Apache IoTDB vs. Graph Engine vs. TimescaleDB vs. XTDB

System Properties Comparison Apache IoTDB vs. Graph Engine vs. TimescaleDB vs. XTDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonTimescaleDB  Xexclude from comparisonXTDB infoformerly named Crux  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 FlinkA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelTime Series DBMSGraph DBMS
Key-value store
Time Series DBMSDocument store
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
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websiteiotdb.apache.orgwww.graphengine.iowww.timescale.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.graphengine.io/­docs/­manualdocs.timescale.comwww.xtdb.com/­docs
DeveloperApache Software FoundationMicrosoftTimescaleJuxt Ltd.
Initial release2018201020172019
Current release1.1.0, April 20232.13.0, November 20231.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMIT LicenseOpen Source infoApache 2.0Open Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava.NET and CCClojure
Server operating systemsAll OS with a Java VM (>= 1.8).NETLinux
OS X
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes, extensible-data-notation format
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 indexesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyes infofull PostgreSQL SQL syntaxlimited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
Native API
RESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP REST
JDBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
F#
Visual Basic
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Clojure
Java
Server-side scripts infoStored proceduresyesyesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replication with hot standby and reads on replicas infoyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlyesfine grained access rights according to SQL-standard

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More resources
Apache IoTDBGraph Engine infoformer name: TrinityTimescaleDBXTDB infoformerly named Crux
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