DBMS > Impala vs. Kyligence Enterprise vs. MySQL

System Properties Comparison Impala vs. Kyligence Enterprise vs. MySQL

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

Widely used open source RDBMS

Primary database model

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	17.49
Rank	#40	Overall
	#25	Relational DBMS

Score	0.25
Rank	#277	Overall
	#131	Relational DBMS

Score	1194.87
Rank	#2	Overall
	#2	Relational DBMS

Website

www.cloudera.com/products/open-source/apache-hadoop/impala.html

kyligence.io/kyligence-enterprise

www.mysql.com

Technical documentation

docs.cloudera.com/documentation/enterprise/latest/topics/impala.html

dev.mysql.com/doc

Developer

Cloudera

Kyligence, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2013

2016

1995

Current release

4.0.0, July 2021

8.0.29, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java

C and C++

Server operating systems

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

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

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

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 and integration of map-reduce

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

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

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

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

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

no user groups or roles

More information provided by the system vendor

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