DBMS > Apache IoTDB vs. BaseX vs. PostgreSQL vs. TimesTen vs. WakandaDB

System Properties Comparison Apache IoTDB vs. BaseX vs. PostgreSQL vs. TimesTen vs. WakandaDB

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

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Widely used open source RDBMS

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

In-Memory RDBMS compatible to Oracle

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Time Series DBMS

Native XML 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

Object oriented 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	1.19
Rank	#176	Overall
	#15	Time Series DBMS

Score	1.90
Rank	#136	Overall
	#4	Native XML DBMS

Score	645.05
Rank	#4	Overall
	#4	Relational DBMS

Score	1.35
Rank	#165	Overall
	#75	Relational DBMS

Score	0.09
Rank	#352	Overall
	#16	Object oriented DBMS

Website

iotdb.apache.org

basex.org

www.postgresql.org

www.oracle.com/database/technologies/related/timesten.html

wakanda.github.io

Technical documentation

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

docs.basex.org

www.postgresql.org/docs

docs.oracle.com/database/timesten-18.1

wakanda.github.io/doc

Developer

Apache Software Foundation

BaseX GmbH

PostgreSQL Global Development Group

www.postgresql.org/developer

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Wakanda SAS

Initial release

2018

2007

1989

1989: Postgres, 1996: PostgreSQL

1998

2012

Current release

1.1.0, April 2023

10.7, August 2023

16.2, February 2024

11 Release 2 (11.2.2.8.0)

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD license

Open Source

BSD

commercial

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++, JavaScript

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

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

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XQuery supports types

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.

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

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

RESTful HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++
Java
PL/SQL

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions

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

PL/SQL

yes

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

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

none

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

yes

In-memory capabilities

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

yes

User concepts

Access control

yes

Users with fine-grained authorization concept on 4 levels

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

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