DBMS > Apache Impala vs. BaseX vs. Kyligence Enterprise vs. MySQL vs. PouchDB

System Properties Comparison Apache Impala vs. BaseX vs. Kyligence Enterprise vs. MySQL vs. PouchDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

A distributed analytics engine for big data, built on top of Apache Kylin

Widely used open source RDBMS

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Relational DBMS

Native XML DBMS

Relational DBMS

Key/Value like access via memcached API

Document store

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	1.90
Rank	#136	Overall
	#4	Native XML DBMS

Score	0.39
Rank	#276	Overall
	#125	Relational DBMS

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Score	2.35
Rank	#116	Overall
	#22	Document stores

Website

impala.apache.org

basex.org

kyligence.io/kyligence-enterprise

www.mysql.com

pouchdb.com

Technical documentation

impala.apache.org/impala-docs.html

docs.basex.org

dev.mysql.com/doc

pouchdb.com/guides

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

BaseX GmbH

Kyligence, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Apache Software Foundation

Initial release

2013

2007

2016

1995

2012

Current release

4.1.0, June 2022

10.7, August 2023

8.3.0, January 2024

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

BSD license

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java

C and C++

JavaScript

Server operating systems

Linux

Linux
OS X
Windows

Linux

FreeBSD
Linux
OS X
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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

Secondary indexes

yes

via views

SQL

Support of SQL

SQL-like DML and DDL statements

ANSI SQL for queries (using Apache Calcite)

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

All languages supporting JDBC/ODBC

Actionscript
C
C#
Haskell
Java
JavaScript

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

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

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

proprietary syntax

View functions in JavaScript

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Multi-source replication
Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual 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

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

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Users with fine-grained authorization concept on 4 levels

Users with fine-grained authorization concept

no user groups or roles

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