DBMS > 4D vs. Cassandra vs. Dragonfly vs. Graph Engine

System Properties Comparison 4D vs. Cassandra vs. Dragonfly vs. Graph Engine

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

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 in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Primary database model

Relational DBMS

Wide column store

Key-value store

Graph DBMS
Key-value store

Secondary database models

Vector DBMS

starting with release V5

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

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

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Website

www.4d.com

cassandra.apache.org

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

www.graphengine.io

Technical documentation

developer.4d.com

cassandra.apache.org/doc/latest

www.dragonflydb.io/docs

www.graphengine.io/docs/manual

Developer

4D, Inc

Apache Software Foundation

Apache top level project, originally developped by Facebook

DragonflyDB team and community contributors

Microsoft

Initial release

1984

2008

2023

2010

Current release

v20, April 2023

4.1.3, July 2023

1.0, March 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

BSL 1.1

Open Source

MIT License

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

C++

.NET and C

Server operating systems

OS X
Windows

BSD
Linux
OS X
Windows

Linux

.NET

Data scheme

yes

schema-free

scheme-free

yes

Typing

predefined data types such as float or date

yes

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

restricted

only equality queries, not always the best performing solution

SQL

Support of SQL

yes

close to SQL 92

SQL-like SELECT, DML and DDL statements (CQL)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

Proprietary protocol

RESP - REdis Serialization Protocol

RESTful HTTP API

Supported programming languages

4D proprietary IDE
PHP

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

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++
F#
Visual Basic

Server-side scripts

Stored procedures

yes

Lua

yes

Triggers

yes

publish/subscribe channels provide some trigger functionality

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

Representation of geographical distribution of servers is possible

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

Atomic execution of command blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

In-memory capabilities

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

yes

User concepts

Access control

Users and groups

Access rights for users can be defined per object

Password-based authentication

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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