DBMS > Apache Doris vs. Kyligence Enterprise vs. Microsoft Azure Cosmos DB vs. MySQL vs. NuoDB

System Properties Comparison Apache Doris vs. Kyligence Enterprise vs. Microsoft Azure Cosmos DB vs. MySQL vs. NuoDB

Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

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

Globally distributed, horizontally scalable, multi-model database service

Widely used open source RDBMS

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Website

doris.apache.org
github.com/apache/doris

kyligence.io/kyligence-enterprise

azure.microsoft.com/services/cosmos-db

www.mysql.com

www.3ds.com/nuodb-distributed-sql-database

Technical documentation

github.com/apache/doris/wiki

learn.microsoft.com/azure/cosmos-db

dev.mysql.com/doc

doc.nuodb.com

Developer

Apache Software Foundation, originally contributed from Baidu

Kyligence, Inc.

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2017

2016

2014

1995

2013

Current release

1.2.2, February 2023

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

limited edition free

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

C++

Server operating systems

Linux

hosted

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON 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

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

ANSI SQL for queries (using Apache Calcite)

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
MySQL client

JDBC
ODBC
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
ODBC

Supported programming languages

Java

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

JavaScript

yes

proprietary syntax

Java, SQL

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

data is dynamically stored/cached on the nodes where it is read/written

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

not for MyISAM storage engine

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

MVCC

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

Temporary table

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Users with fine-grained authorization concept

no user groups or roles

Standard SQL roles/ privileges, Administrative Users

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