DBMS > BaseX vs. EsgynDB vs. RRDtool vs. WakandaDB

System Properties Comparison BaseX vs. EsgynDB vs. RRDtool vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

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

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

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

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

Primary database model

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

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	0.10
Rank	#356	Overall
	#17	Object oriented DBMS

Website

basex.org

www.esgyn.cn

oss.oetiker.ch/rrdtool

wakanda.github.io

Technical documentation

docs.basex.org

oss.oetiker.ch/rrdtool/doc

wakanda.github.io/doc

Developer

BaseX GmbH

Esgyn

Tobias Oetiker

Wakanda SAS

Initial release

2007

2015

1999

2012

Current release

11.0, June 2024

1.8.0, 2022

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

BSD license

commercial

Open Source

GPL V2 and FLOSS

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++, Java

Implementations in Java (e.g. RRD4J) and C# available

C++, JavaScript

Server operating systems

Linux
OS X
Windows

Linux

HP-UX
Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

XQuery supports types

yes

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

ADO.NET
JDBC
ODBC

in-process shared library
Pipes

RESTful HTTP API

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

All languages supporting JDBC/ODBC/ADO.Net

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

by using the rrdcached daemon

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

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

fine grained access rights according to SQL-standard

yes

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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