DBMS > Apache IoTDB vs. Derby vs. EsgynDB vs. PostgreSQL vs. Tibero

System Properties Comparison Apache IoTDB vs. Derby vs. EsgynDB vs. PostgreSQL vs. Tibero

Editorial information provided by DB-Engines

Name

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

A secure RDBMS, designed for easy portability from Oracle

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.

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

us.tmaxsoft.com/products/tibero

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

db.apache.org/derby/manuals/index.html

www.postgresql.org/docs

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Apache Software Foundation

Esgyn

PostgreSQL Global Development Group

www.postgresql.org/developer

TmaxSoft

Initial release

2018

1997

2015

1989

1989: Postgres, 1996: PostgreSQL

2003

Current release

1.1.0, April 2023

10.17.1.0, November 2023

16.3, May 2024

6, April 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache version 2

commercial

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++, Java

C and Assembler

Server operating systems

All OS with a Java VM (>= 1.8)

All OS with a Java VM

Linux

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

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.

yes

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

standard with numerous extensions

yes

APIs and other access methods

JDBC
Native API

JDBC

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

Java Stored Procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Persistent Stored Procedure (PSM)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

none

Sharding

partitioning by range, list and (since PostgreSQL 11) by hash

horizontal partitioning

by range, hash, list or composite

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

Multi-source replication between multi datacenters

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

planned for next version

User concepts

Access control

yes

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

More information provided by the system vendor

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