DBMS > Alibaba Cloud Table Store vs. Dragonfly vs. Ehcache vs. MySQL

System Properties Comparison Alibaba Cloud Table Store vs. Dragonfly vs. Ehcache vs. MySQL

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Editorial information provided by DB-Engines

Name

Description

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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

A widely adopted Java cache with tiered storage options

Widely used open source RDBMS

Primary database model

Wide column store

Key-value store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

www.alibabacloud.com/product/table-store

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.ehcache.org

www.mysql.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

www.dragonflydb.io/docs

www.ehcache.org/documentation

dev.mysql.com/doc

Developer

Alibaba

DragonflyDB team and community contributors

Terracotta Inc, owned by Software AG

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2016

2023

2009

1995

Current release

1.0, March 2023

3.10.0, March 2022

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

BSL 1.1

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Java

C and C++

Server operating systems

hosted

Linux

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

scheme-free

schema-free

yes

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

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

with proprietary extensions

APIs and other access methods

HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

JCache

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java
Python

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

Java

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

Lua

yes

proprietary syntax

Triggers

publish/subscribe channels provide some trigger functionality

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

by using Terracotta Server

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

yes

by using Terracotta Server

Multi-source replication
Source-replica replication

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 (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic single-row operations

Atomic execution of command blocks and scripts

yes

supports JTA and can work as an XA resource

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

Access rights based on subaccounts and tokens

Password-based authentication

Users with fine-grained authorization concept

no user groups or roles

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