DBMS > BaseX vs. Citus vs. Hazelcast

System Properties Comparison BaseX vs. Citus vs. Hazelcast

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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.

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

A widely adopted in-memory data grid

Primary database model

Native XML DBMS

Relational DBMS

Key-value store

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	1.90
Rank	#136	Overall
	#4	Native XML DBMS

Score	2.15
Rank	#123	Overall
	#60	Relational DBMS

Score	6.87
Rank	#55	Overall
	#6	Key-value stores

Website

basex.org

www.citusdata.com

hazelcast.com

Technical documentation

docs.basex.org

docs.citusdata.com

hazelcast.org/imdg/docs

Developer

BaseX GmbH

Hazelcast

Initial release

2007

2010

2008

Current release

10.7, August 2023

8.1, December 2018

5.3.6, November 2023

License

Commercial or Open Source

Open Source

BSD license

Open Source

AGPL, commercial license also available

Open Source

Apache Version 2; commercial licenses available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
Windows

Linux

All OS with a Java VM

Data scheme

schema-free

yes

schema-free

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.

yes

specific XML type available, but no XML query functionality

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

SQL-like query language

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

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

JCache
JPA
Memcached protocol
RESTful HTTP API

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

yes

user defined functions

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

yes

Event Listeners, Executor Services

Triggers

yes

via events

yes

Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

other methods possible by using 3rd party extensions

yes

Replicated Map

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Foreign keys

Referential integrity

yes

Transaction concepts

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

multiple readers, single writer

ACID

one or two-phase-commit; repeatable reads; read commited

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

fine grained access rights according to SQL-standard

Role-based access control

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