DBMS > Amazon Aurora vs. Amazon CloudSearch vs. MySQL vs. OrigoDB vs. ScyllaDB

System Properties Comparison Amazon Aurora vs. Amazon CloudSearch vs. MySQL vs. OrigoDB vs. ScyllaDB

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

A hosted search engine service by Amazon with the data stored in Amazons cloud

Widely used open source RDBMS

A fully ACID in-memory object graph database

Cassandra and DynamoDB compatible wide column store

Primary database model

Relational DBMS

Search engine

Relational DBMS

Key/Value like access via memcached API

Document store
Object oriented DBMS

Wide column store

Secondary database models

Document store

Document store
Spatial DBMS

Key-value store

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Website

aws.amazon.com/rds/aurora

aws.amazon.com/cloudsearch

www.mysql.com

origodb.com

www.scylladb.com

Technical documentation

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

docs.aws.amazon.com/cloudsearch

dev.mysql.com/doc

origodb.com/docs

docs.scylladb.com

Developer

Amazon

Oracle

since 2010, originally MySQL AB, then Sun

Robert Friberg et al

ScyllaDB

Initial release

2015

2012

1995

2009

under the name LiveDB

2015

Current release

8.4.0, April 2024

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Open Source (AGPL), commercial license available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C and C++

C++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

all search fields are automatically indexed

yes

cluster global secondary indices

SQL

Support of SQL

yes

with proprietary extensions

SQL-like DML and DDL statements (CQL)

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API
HTTP API
LINQ

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

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

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

yes, Lua

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

automatic partitioning across Amazon Search Instance as required

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

managed transparently by AWS

Multi-source replication
Source-replica replication

Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

depending on model

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Atomicity and isolation are supported for single operations

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

Write ahead log

yes

In-memory capabilities

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

yes

in-memory tables

User concepts

Access control

fine grained access rights according to SQL-standard

authentication via encrypted signatures

Users with fine-grained authorization concept

no user groups or roles

Role based authorization

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more

Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

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