DBMS > BaseX vs. CouchDB vs. JanusGraph vs. MySQL vs. Qdrant

System Properties Comparison BaseX vs. CouchDB vs. JanusGraph vs. MySQL vs. Qdrant

Editorial information provided by DB-Engines

Name

Description

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

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Widely used open source RDBMS

A high-performance vector database with neural network or semantic-based matching

Primary database model

Key/Value like access via memcached API

Vector DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Spatial DBMS

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

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Website

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

docs.basex.org

docs.couchdb.org/en/stable

docs.janusgraph.org

dev.mysql.com/doc

qdrant.tech/documentation

Developer

BaseX GmbH

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Linux Foundation; originally developed as Titan by Aurelius

Oracle

since 2010, originally MySQL AB, then Sun

Qdrant

Initial release

2007

2005

2017

1995

2021

Current release

10.7, August 2023

3.3.3, December 2023

0.6.3, February 2023

8.4.0, April 2024

License

Commercial or Open Source

Open Source

BSD license

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

Java

Erlang

Java

C and C++

Rust

Server operating systems

Linux
OS X
Windows

Android
BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Docker
Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

XQuery supports types

yes

Numbers, Strings, Geo, Boolean

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

Secondary indexes

yes

via views

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

RESTful HTTP/JSON API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
ODBC
Proprietary native API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Clojure
Java
Python

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

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

View functions in JavaScript

yes

proprietary syntax

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

improved architecture with release 2.0

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

yes

Multi-source replication
Source-replica replication

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

multiple readers, single writer

atomic operations within a single document possible

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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 for users can be defined per database

User authentification and security via Rexster Graph Server

Users with fine-grained authorization concept

no user groups or roles

Key-based authentication

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