DBMS > Apache IoTDB vs. PostgreSQL vs. Tkrzw
System Properties Comparison Apache IoTDB vs. PostgreSQL vs. Tkrzw
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|Editorial information provided by DB-Engines|
|Name||Apache IoTDB Xexclude from comparison||PostgreSQL Xexclude from comparison||Tkrzw Successor of Tokyo Cabinet and Kyoto Cabinet Xexclude from comparison|
|Description||An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink||Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL||A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet|
|Primary database model||Time Series DBMS||Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.||Key-value store|
|Secondary database models||Document store|
Graph DBMS with Apache Age
|Developer||Apache Software Foundation||PostgreSQL Global Development Group www.postgresql.org/developer||Mikio Hirabayashi|
|Initial release||2018||1989 1989: Postgres, 1996: PostgreSQL||2020|
|Current release||1.1.0, April 2023||15.3, May 2023||0.9.3, August 2020|
|License Commercial or Open Source||Open Source Apache Version 2.0||Open Source BSD||Open Source Apache Version 2.0|
|Cloud-based only Only available as a cloud service||no||no||no|
|DBaaS offerings (sponsored links) Database as a Service|
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|Server operating systems||All OS with a Java VM (>= 1.8)||FreeBSD|
|Typing predefined data types such as float or date||yes||yes||no|
|XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.||no||yes specific XML-type available, but no XML query functionality.||no|
|SQL Support of SQL||SQL-like query language||yes standard with numerous extensions||no|
|APIs and other access methods||JDBC|
native C library
streaming API for large objects
|Supported programming languages||C|
|Server-side scripts Stored procedures||yes||user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.||no|
|Partitioning methods Methods for storing different data on different nodes||horizontal partitioning (by time range) + vertical partitioning (by deviceId)||partitioning by range, list and (since PostgreSQL 11) by hash||none|
|Replication methods Methods for redundantly storing data on multiple nodes||selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas||Source-replica replication other methods possible by using 3rd party extensions||none|
|MapReduce Offers an API for user-defined Map/Reduce methods||Integration with Hadoop and Spark||no||no|
|Consistency concepts Methods to ensure consistency in a distributed system||Eventual Consistency|
Strong Consistency with Raft
|Immediate Consistency||Immediate Consistency|
|Foreign keys Referential integrity||no||yes||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||no||ACID|
|Concurrency Support for concurrent manipulation of data||yes||yes||yes|
|Durability Support for making data persistent||yes||yes||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||yes||no||yes using specific database classes|
|User concepts Access control||yes||fine grained access rights according to SQL-standard||no|
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|Apache IoTDB||PostgreSQL||Tkrzw Successor of Tokyo Cabinet and Kyoto Cabinet|
|DB-Engines blog posts|
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|Conferences and events|
PGCon 2023, PostgreSQL Conference for Users and Developers
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