DBMS > Dragonfly vs. EsgynDB vs. KairosDB vs. Microsoft SQL Server vs. Quasardb

System Properties Comparison Dragonfly vs. EsgynDB vs. KairosDB vs. Microsoft SQL Server vs. Quasardb

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

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

Distributed Time Series DBMS based on Cassandra or H2

Microsofts flagship relational DBMS

Distributed, high-performance timeseries database

Primary database model

Secondary database models

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	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

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

www.esgyn.cn

github.com/kairosdb/kairosdb

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

quasar.ai

Technical documentation

www.dragonflydb.io/docs

kairosdb.github.io

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

doc.quasar.ai/master

Developer

DragonflyDB team and community contributors

Esgyn

Microsoft

quasardb

Initial release

2023

2015

2013

1989

2009

Current release

1.0, March 2023

1.2.2, November 2018

SQL Server 2022, November 2022

3.14.1, January 2024

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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++, Java

Java

C++

Server operating systems

Linux

Linux
OS X
Windows

Linux
Windows

BSD
Linux
OS X
Windows

Data scheme

scheme-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

integer and binary

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

with tags

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

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

HTTP API

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/ADO.Net

Java
JavaScript

Node.js
PHP
Python

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

Lua

Java Stored Procedures

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

based on Cassandra

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

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication between multi datacenters

selectable replication factor

based on Cassandra

yes, but depending on the SQL-Server Edition

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

by using LevelDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

User concepts

Access control

Password-based authentication

fine grained access rights according to SQL-standard

simple password-based access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

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