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DBMS > Apache IoTDB vs. Databend vs. DuckDB vs. EsgynDB vs. Postgres-XL

System Properties Comparison Apache IoTDB vs. Databend vs. DuckDB vs. EsgynDB vs. Postgres-XL

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatabend  Xexclude from comparisonDuckDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonPostgres-XL  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 complexityAn embeddable, in-process, column-oriented SQL OLAP RDBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelTime Series DBMSRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score4.63
Rank#69  Overall
#37  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websiteiotdb.apache.orggithub.com/­datafuselabs/­databend
www.databend.com
duckdb.orgwww.esgyn.cnwww.postgres-xl.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.databend.comduckdb.org/­docswww.postgres-xl.org/­documentation
DeveloperApache Software FoundationDatabend LabsEsgyn
Initial release20182021201820152014 infosince 2012, originally named StormDB
Current release1.1.0, April 20231.0.59, April 20231.0.0, June 202410 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoMIT LicensecommercialOpen Source infoMozilla public license
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 languageJavaRustC++C++, JavaC
Server operating systemsAll OS with a Java VM (>= 1.8)hosted
Linux
macOS
server-lessLinuxLinux
macOS
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonononoyes infoXML type, but no XML query functionality
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like query languageyesyesyesyes infodistributed, parallel query execution
APIs and other access methodsJDBC
Native API
CLI Client
JDBC
RESTful HTTP API
Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
ADO.NET
JDBC
ODBC
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
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
All languages supporting JDBC/ODBC/ADO.Net.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyesnonoJava Stored Proceduresuser defined functions
Triggersyesnononoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)nonenoneShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnonenoneMulti-source replication between multi datacenters
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDACIDACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlyesUsers with fine-grained authorization concept, user rolesnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache IoTDBDatabendDuckDBEsgynDBPostgres-XL
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