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DBMS > Apache IoTDB vs. Databend vs. gStore vs. TimescaleDB

System Properties Comparison Apache IoTDB vs. Databend vs. gStore vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatabend  Xexclude from comparisongStore  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 FlinkAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityA native Graph DBMS to store and maintain very large RDF datasets.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSRelational DBMSGraph DBMS
RDF store
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.28
Rank#287  Overall
#131  Relational DBMS
Score0.03
Rank#367  Overall
#37  Graph DBMS
#18  RDF stores
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Websiteiotdb.apache.orggithub.com/­datafuselabs/­databend
www.databend.com
en.gstore.cnwww.timescale.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databend.comen.gstore.cn/­#/­enDocsdocs.timescale.com
DeveloperApache Software FoundationDatabend LabsTimescale
Initial release2018202120162017
Current release1.1.0, April 20231.0.59, April 20231.2, November 20232.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoBSDOpen 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 languageJavaRustC++C
Server operating systemsAll OS with a Java VM (>= 1.8)hosted
Linux
macOS
LinuxLinux
OS X
Windows
Data schemeyesyesschema-free and OWL/RDFS-schema supportyes
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.nononoyes
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like query languageyesnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
Native API
CLI Client
JDBC
RESTful HTTP API
HTTP API
SPARQL 1.1
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Java
JavaScript (Node.js)
Python
Rust
C++
Java
JavaScript (Node.js)
PHP
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnoyesuser 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)noneyes, 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 replicasnoneSource-replica replication with hot standby and reads on replicas info
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 Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlyesUsers with fine-grained authorization concept, user rolesUsers, roles and permissions, Role-Based Access Control (RBAC) supportedfine grained access rights according to SQL-standard

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More resources
Apache IoTDBDatabendgStoreTimescaleDB
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