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DBMS > Apache IoTDB vs. Bangdb vs. EsgynDB vs. Postgres-XL vs. TDengine

System Properties Comparison Apache IoTDB vs. Bangdb vs. EsgynDB vs. Postgres-XL vs. TDengine

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBangdb  Xexclude from comparisonEsgynDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonTDengine  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 FlinkConverged and high performance database for device data, events, time series, document and graphEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresTime Series DBMS and big data platform
Primary database modelTime Series DBMSDocument store
Graph DBMS
Time Series DBMS
Relational DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score2.68
Rank#106  Overall
#9  Time Series DBMS
Websiteiotdb.apache.orgbangdb.comwww.esgyn.cnwww.postgres-xl.orggithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.bangdb.comwww.postgres-xl.org/­documentationdocs.tdengine.com
DeveloperApache Software FoundationSachin Sinha, BangDBEsgynTDEngine, previously Taos Data
Initial release2018201220152014 infosince 2012, originally named StormDB2019
Current release1.1.0, April 2023BangDB 2.0, October 202110 R1, October 20183.0, August 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSD 3commercialOpen Source infoMozilla public licenseOpen Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++C++, JavaCC
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinuxLinux
macOS
Linux
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsyesyesyes
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 infoXML type, but no XML query functionalityno
Secondary indexesyesyes infosecondary, composite, nested, reverse, geospatialyesyesno
SQL infoSupport of SQLSQL-like query languageSQL like support with command line toolyesyes infodistributed, parallel query executionStandard SQL with extensions for time-series applications
APIs and other access methodsJDBC
Native API
Proprietary protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Java
Python
All languages supporting JDBC/ODBC/ADO.Net.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresyesnoJava Stored Proceduresuser defined functionsno
Triggersyesyes, Notifications (with Streaming only)noyesyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factor, Knob for CAP (enterprise version only)Multi-source replication between multi datacentersyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Tunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, run db with in-memory only modenono
User concepts infoAccess controlyesyes (enterprise version only)fine grained access rights according to SQL-standardfine grained access rights according to SQL-standardyes
More information provided by the system vendor
Apache IoTDBBangdbEsgynDBPostgres-XLTDengine
Specific characteristicsTDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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More resources
Apache IoTDBBangdbEsgynDBPostgres-XLTDengine
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