DBMS > Dragonfly vs. EXASOL vs. Microsoft SQL Server vs. OrientDB vs. SQream DB

System Properties Comparison Dragonfly vs. EXASOL vs. Microsoft SQL Server vs. OrientDB vs. SQream DB

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Microsofts flagship relational DBMS

Multi-model DBMS (Document, Graph, Key/Value)

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Secondary database models

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	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

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

www.exasol.com

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

orientdb.org

sqream.com

Technical documentation

www.dragonflydb.io/docs

www.exasol.com/resources

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

www.orientdb.com/docs/last/index.html

docs.sqream.com

Developer

DragonflyDB team and community contributors

Exasol

Microsoft

OrientDB LTD; CallidusCloud; SAP

SQream Technologies

Initial release

2023

2000

1989

2010

2017

Current release

1.0, March 2023

SQL Server 2022, November 2022

3.2.29, March 2024

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

restricted free version is available

Open Source

Apache version 2

commercial

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++, CUDA, Haskell, Java, Scala

Server operating systems

Linux

Linux
Windows

All OS with a Java JDK (>= JDK 6)

Linux

Data scheme

scheme-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

Typing

predefined data types such as float or date

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

yes

yes, ANSI Standard SQL Types

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

SQL-like query language, no joins

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

.Net
JDBC
ODBC
WebSocket

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

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

.Net
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

Java
Lua
Python
R

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

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

user defined functions

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

Java, Javascript

user defined functions in Python

Triggers

publish/subscribe channels provide some trigger functionality

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, but depending on the SQL-Server Edition

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

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

User concepts

Access control

Password-based authentication

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

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

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