DBMS > Dragonfly vs. Elasticsearch vs. EsgynDB vs. Microsoft SQL Server vs. mSQL

System Properties Comparison Dragonfly vs. Elasticsearch vs. EsgynDB vs. Microsoft SQL Server vs. mSQL

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 distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Microsofts flagship relational DBMS

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Key-value store

Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Graph DBMS
Spatial DBMS

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

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

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Website

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

www.elastic.co/elasticsearch

www.esgyn.cn

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

hughestech.com.au/products/msql

Technical documentation

www.dragonflydb.io/docs

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

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

Developer

DragonflyDB team and community contributors

Elastic

Esgyn

Microsoft

Hughes Technologies

Initial release

2023

2010

2015

1989

1994

Current release

1.0, March 2023

8.6, January 2023

SQL Server 2022, November 2022

4.4, October 2021

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

Elastic License

commercial

restricted free version is available

commercial

free licenses can be provided

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C++, Java

C++

Server operating systems

Linux

All OS with a Java VM

Linux

Linux
Windows

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

Data scheme

scheme-free

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

A subset of ANSI SQL is implemented

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

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

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

JDBC
ODBC

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

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

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

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

Lua

yes

Java Stored Procedures

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

Triggers

publish/subscribe channels provide some trigger functionality

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication between multi datacenters

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

none

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

Memcached and Redis integration

yes

User concepts

Access control

Password-based authentication

fine grained access rights according to SQL-standard

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