DBMS > Alibaba Cloud Table Store vs. Dragonfly vs. Microsoft SQL Server vs. RethinkDB

System Properties Comparison Alibaba Cloud Table Store vs. Dragonfly vs. Microsoft SQL Server vs. RethinkDB

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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

Microsofts flagship relational DBMS

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Website

www.alibabacloud.com/product/table-store

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

www.microsoft.com/en-us/sql-server

rethinkdb.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

www.dragonflydb.io/docs

learn.microsoft.com/en-US/sql/sql-server

rethinkdb.com/docs

Developer

Alibaba

DragonflyDB team and community contributors

Microsoft

The Linux Foundation

since July 2017

Initial release

2016

2023

1989

2009

Current release

1.0, March 2023

SQL Server 2022, November 2022

2.4.1, August 2020

License

Commercial or Open Source

commercial

Open Source

BSL 1.1

commercial

restricted free version is 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++

Server operating systems

hosted

Linux

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

scheme-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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

yes

string, binary, float, bool, date, geometry

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

APIs and other access methods

HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

Lua

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

publish/subscribe channels provide some trigger functionality

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

yes, but depending on the SQL-Server Edition

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

Atomic execution of command blocks and scripts

ACID

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

MVCC based

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

Access rights based on subaccounts and tokens

Password-based authentication

fine grained access rights according to SQL-standard

yes

users and table-level permissions

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