DBMS > BaseX vs. Manticore Search vs. Microsoft Azure Cosmos DB vs. MySQL

System Properties Comparison BaseX vs. Manticore Search vs. Microsoft Azure Cosmos DB vs. MySQL

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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.

Multi-storage database for search, including full-text search.

Globally distributed, horizontally scalable, multi-model database service

Widely used open source RDBMS

Primary database model

Native XML DBMS

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Spatial DBMS

Document store
Spatial DBMS

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

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

basex.org

manticoresearch.com

azure.microsoft.com/services/cosmos-db

www.mysql.com

Technical documentation

docs.basex.org

manual.manticoresearch.com

learn.microsoft.com/azure/cosmos-db

dev.mysql.com/doc

Developer

BaseX GmbH

Manticore Software

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2007

2017

2014

1995

Current release

11.0, June 2024

6.0, February 2023

8.4.0, April 2024

License

Commercial or Open Source

Open Source

BSD license

Open Source

GPL version 2

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

C and C++

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
macOS
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

XQuery supports types

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

yes

JSON 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.

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

JavaScript

yes

proprietary syntax

Triggers

yes

via events

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

none

Synchronous replication based on Galera library

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

multiple readers, single writer

yes

isolated transactions for atomic changes and binary logging for safe writes

Multi-item ACID transactions with snapshot isolation within a partition

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

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

Access rights can be defined down to the item level

Users with fine-grained authorization concept

no user groups or roles

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