DBMS > BaseX vs. etcd vs. Postgres-XL vs. PostgreSQL vs. TDSQL for MySQL

System Properties Comparison BaseX vs. etcd vs. Postgres-XL vs. PostgreSQL vs. TDSQL for MySQL

Editorial information provided by DB-Engines

Name

Description

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

A distributed reliable key-value store

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Native XML DBMS

Key-value store

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector 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	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	0.85
Rank	#205	Overall
	#95	Relational DBMS

Website

basex.org

etcd.io
github.com/etcd-io/etcd

www.postgres-xl.org

www.postgresql.org

www.tencentcloud.com/products/dcdb

Technical documentation

docs.basex.org

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.postgres-xl.org/documentation

www.postgresql.org/docs

www.tencentcloud.com/document/product/1042

Developer

BaseX GmbH

PostgreSQL Global Development Group

www.postgresql.org/developer

Tencent

Initial release

2007

2014

since 2012, originally named StormDB

1989

1989: Postgres, 1996: PostgreSQL

2013

Current release

10.7, August 2023

3.4, August 2019

10 R1, October 2018

16.3, May 2024

License

Commercial or Open Source

Open Source

BSD license

Open Source

Apache Version 2.0

Open Source

Mozilla public license

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
Windows

experimental

Linux
macOS

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

hosted

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.

yes

XML type, but no XML query functionality

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

standard with numerous extensions

yes

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

gRPC
JSON over HTTP

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

JDBC
ODBC

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C#
C++
Java
PHP
Python
Ruby

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

Triggers

yes

via events

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

partitioning by range, list and (since PostgreSQL 11) by hash

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

ACID

MVCC

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.

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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

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