DBMS > Datastax Enterprise vs. Dragonfly vs. mSQL vs. SQLite

System Properties Comparison Datastax Enterprise vs. Dragonfly vs. mSQL vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used embeddable, in-process RDBMS

Primary database model

Wide column store

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Score	4.82
Rank	#65	Overall
	#4	Wide column stores

Score	0.44
Rank	#255	Overall
	#38	Key-value stores

Score	1.26
Rank	#163	Overall
	#74	Relational DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

www.datastax.com/products/datastax-enterprise

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

hughestech.com.au/products/msql

www.sqlite.org

Technical documentation

docs.datastax.com

www.dragonflydb.io/docs

www.sqlite.org/docs.html

Developer

DataStax

DragonflyDB team and community contributors

Hughes Technologies

Dwayne Richard Hipp

Initial release

2011

2023

1994

2000

Current release

6.8, April 2020

1.0, March 2023

4.4, October 2021

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

commercial

Open Source

BSL 1.1

commercial

free licenses can be provided

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

Implementation language

Java

C++

Server operating systems

Linux
OS X

Linux

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

server-less

Data scheme

schema-free

scheme-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

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

yes

not rigid because of 'dynamic typing' concept.

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements (CQL); Spark SQL

A subset of ANSI SQL is implemented

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

yes

SQL-92 is not fully supported

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

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
Java
Perl
PHP
Tcl

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

Lua

Triggers

yes

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware, advanced replication for edge computing

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Eventual Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

via file-system locks

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 for users can be defined per object

Password-based authentication

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Licensing and pricing models

Annual subscription
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