DBMS > Alibaba Cloud AnalyticDB for MySQL vs. Amazon Aurora vs. Apache Cassandra vs. etcd

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. Amazon Aurora vs. Apache Cassandra vs. etcd

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A real-time data warehousing service that can process petabytes of data with high concurrency and low latency. It is fully compatible with the MySQL protocol.

MySQL and PostgreSQL compatible cloud service by Amazon

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A distributed reliable key-value store

Primary database model

Relational DBMS

Wide column store

Key-value store

Secondary database models

Document store

Vector DBMS

starting with release V5

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

Score	0.92
Rank	#195	Overall
	#91	Relational DBMS

Score	7.84
Rank	#44	Overall
	#28	Relational DBMS

Score	98.94
Rank	#11	Overall
	#1	Wide column stores

Score	7.05
Rank	#53	Overall
	#5	Key-value stores

Website

www.alibabacloud.com/product/analyticdb-for-mysql

aws.amazon.com/rds/aurora

cassandra.apache.org

etcd.io
github.com/etcd-io/etcd

Technical documentation

www.alibabacloud.com/help/doc-detail/93776.htm

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

cassandra.apache.org/doc/latest

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

Developer

Alibaba

Amazon

Apache Software Foundation

Apache top level project, originally developped by Facebook

Initial release

2015

2008

Current release

5.0-rc1, July 2024

3.4, August 2019

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

Server operating systems

hosted

BSD
Linux
OS X
Windows

FreeBSD
Linux
Windows

experimental

Data scheme

yes

schema-free

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

restricted

only equality queries, not always the best performing solution

SQL

Support of SQL

yes

SQL-like SELECT, DML and DDL statements (CQL)

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

gRPC
JSON over HTTP

Supported programming languages

C#
Java
PHP
Python

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

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Server-side scripts

Stored procedures

yes

Triggers

yes

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

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

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

A real-time data warehousing service that can process PB data with high concurrency...
» more

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

Competitive advantages

TPC Benchmark: The world leading result in TPC-DS benchmark . TPC-H benchmark for...
» more

No single point of failure ensures 100% availability . Operational simplicity for...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Market metrics

Apache Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Available regions: America US Virginia US Silicon Valley Asia China Hong Kong India...
» more

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
» more

News

How to Create Vector Embeddings in Node.js
25 September 2024

Glean and DataStax Partner to Help Developers Harness Powerful Enterprise Search
23 September 2024

DataStax Named a Leader in The Forrester Wave™: Vector Databases, Q3 2024
23 September 2024

How to Build a Notion Clone with Astra DB and Mongoose
20 September 2024

How to Monitor DataStax-Powered RAG Applications with Fiddler
19 September 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.