DBMS > Amazon Aurora vs. MySQL vs. OpenQM vs. RavenDB vs. Solr

System Properties Comparison Amazon Aurora vs. MySQL vs. OpenQM vs. RavenDB vs. Solr

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Widely used open source RDBMS

QpenQM is a high-performance, self-tuning, multi-value DBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Relational DBMS

Key/Value like access via memcached API

Multivalue DBMS

Document store

Search engine

Secondary database models

Document store

Document store
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

Spatial DBMS

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

aws.amazon.com/rds/aurora

www.mysql.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

ravendb.net

solr.apache.org

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

dev.mysql.com/doc

ravendb.net/docs

solr.apache.org/resources.html

Developer

Amazon

Oracle

since 2010, originally MySQL AB, then Sun

Rocket Software, originally Martin Phillips

Hibernating Rhinos

Apache Software Foundation

Initial release

2015

1995

1993

2010

2006

Current release

8.4.0, April 2024

3.4-12

5.4, July 2022

9.6.0, April 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPLv2, extended commercial license available

Open Source

AGPL version 3, commercial license available

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

Java

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
macOS
Raspberry Pi
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

with some exceptions

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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 search fields are automatically indexed

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language (RQL)

Solr Parallel SQL Interface

APIs and other access methods

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Java API
RESTful HTTP/JSON API

Supported programming languages

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

.Net
Basic
C
Java
Objective C
PHP
Python

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

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

yes

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

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

ACID

not for MyISAM storage engine

ACID

ACID, Cluster-wide transaction available

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Access rights can be defined down to the item level

Authorization levels configured per client per database

yes

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