DBMS > Alibaba Cloud AnalyticDB for MySQL vs. Alibaba Cloud Table Store vs. FatDB vs. RocksDB vs. Vitess

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. Alibaba Cloud Table Store vs. FatDB vs. RocksDB vs. Vitess

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

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.

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Wide column store

Document store
Key-value store

Key-value store

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	0.91
Rank	#201	Overall
	#94	Relational DBMS

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

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

www.alibabacloud.com/product/table-store

rocksdb.org

vitess.io

Technical documentation

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

www.alibabacloud.com/help/en/tablestore

github.com/facebook/rocksdb/wiki

vitess.io/docs

Developer

Alibaba

FatCloud

Facebook, Inc.

The Linux Foundation, PlanetScale

Initial release

2016

2012

2013

Current release

9.2.1, May 2024

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

Apache Version 2.0, commercial licenses available

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.

Implementation language

C++

Server operating systems

hosted

Windows

Linux

Docker
Linux
macOS

Data scheme

yes

schema-free

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

yes

Via inetgration in SQL Server

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

HTTP API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

C++ API
Java API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C#
Java
PHP
Python

Java
Python

C
C++
Go
Java
Perl
Python
Ruby

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

via applications

yes

proprietary syntax

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Implicit feature of the cloud service

selectable replication factor

yes

Multi-source replication
Source-replica replication

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

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Atomic single-row operations

yes

ACID at shard level

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

fine grained access rights according to SQL-standard

Access rights based on subaccounts and tokens

Can implement custom security layer via applications

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

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

Competitive advantages

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

Licensing and pricing models

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

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.