DBMS > BaseX vs. DolphinDB vs. EventStoreDB vs. MonetDB

System Properties Comparison BaseX vs. DolphinDB vs. EventStoreDB vs. MonetDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Industrial-strength, open-source database solution built from the ground up for event sourcing.

A relational database management system that stores data in columns

Primary database model

Native XML DBMS

Time Series DBMS
Vector DBMS

Event Store

Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	1.56
Rank	#141	Overall
	#4	Native XML DBMS

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	1.07
Rank	#181	Overall
	#1	Event Stores

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Website

Technical documentation

docs.basex.org

docs.dolphindb.cn/en/help200/index.html

developers.eventstore.com

www.monetdb.org/Documentation

Developer

BaseX GmbH

DolphinDB, Inc

Event Store Limited

MonetDB BV

Initial release

2007

2018

2012

2004

Current release

11.2, August 2024

v2.00.4, January 2022

21.2, February 2021

Dec2023 (11.49), December 2023

License

Commercial or Open Source

Open Source

BSD license

commercial

free community version available

Open Source

Mozilla Public License 2.0

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++

Server operating systems

Linux
OS X
Windows

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL 2003 with some extensions

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

yes

yes, in SQL, C, R

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

multiple readers, single writer

yes

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

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

Administrators, Users, Groups

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

XML Injection Attacks: What to Know About XPath, XQuery, XXE & More
18 May 2022, Hashed Out by The SSL Store™

9 Skills You Need to Become a Data Engineer
2 November 2022, KDnuggets

provided by Google News

MonetDB Foundation launched
31 January 2024, Centrum Wiskunde & Informatica (CWI)

PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R — Part I
6 April 2018, Data Science Central

How MonetDB/X100 Exploits Modern CPU Performance
14 January 2020, Towards Data Science

Test of Time Award for paper on vectorized execution
16 January 2024, Centrum Wiskunde & Informatica (CWI)

Monet DB The Column-Store Pioneer
4 September 2019, Open Source For You

provided by Google News

Share this page