DBMS > Dragonfly vs. HEAVY.AI vs. Microsoft SQL Server vs. mSQL vs. Sadas Engine

System Properties Comparison Dragonfly vs. HEAVY.AI vs. Microsoft SQL Server vs. mSQL vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

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 high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Microsofts flagship relational DBMS

mSQL (Mini SQL) is a simple and lightweight RDBMS

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

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

github.com/heavyai/heavydb
www.heavy.ai

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

hughestech.com.au/products/msql

www.sadasengine.com

Technical documentation

www.dragonflydb.io/docs

docs.heavy.ai

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

DragonflyDB team and community contributors

HEAVY.AI, Inc.

Microsoft

Hughes Technologies

SADAS s.r.l.

Initial release

2023

2016

1989

1994

2006

Current release

1.0, March 2023

5.10, January 2022

SQL Server 2022, November 2022

4.4, October 2021

8.0

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

commercial

free licenses can be provided

commercial

free trial version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++ and CUDA

C++

Server operating systems

Linux

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

AIX
Linux
Windows

Data scheme

scheme-free

yes

Typing

predefined data types such as float or date

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

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC
Thrift
Vega

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

JDBC
ODBC

JDBC
ODBC
Proprietary protocol

Supported programming languages

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

All languages supporting JDBC/ODBC/Thrift
Python

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

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net
C
C#
C++
Groovy
Java
PHP
Python

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

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

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

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

managed by 'Learn by Usage'

User concepts

Access control

Password-based authentication

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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