DBMS > Dragonfly vs. EXASOL vs. Neo4j vs. SQLite vs. VelocityDB

System Properties Comparison Dragonfly vs. EXASOL vs. Neo4j vs. SQLite vs. VelocityDB

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.

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Widely used embeddable, in-process RDBMS

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Graph DBMS
Object oriented 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	44.89
Rank	#21	Overall
	#1	Graph DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

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

Technical documentation

www.dragonflydb.io/docs

www.exasol.com/resources

neo4j.com/docs

www.sqlite.org/docs.html

velocitydb.com/UserGuide

Developer

DragonflyDB team and community contributors

Exasol

Neo4j, Inc.

Dwayne Richard Hipp

VelocityDB Inc

Initial release

2023

2000

2007

2000

2011

Current release

1.0, March 2023

5.20, May 2024

3.46.0 (23 May 2024), May 2024

7.x

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

Open Source

GPL version3, commercial licenses available

Open Source

Public Domain

commercial

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.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

C++

Java, Scala

Server operating systems

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

server-less

Any that supports .NET

Data scheme

scheme-free

yes

schema-free and schema-optional

yes

dynamic column types

yes

Typing

predefined data types such as float or date

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

yes

not rigid because of 'dynamic typing' concept.

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.

Secondary indexes

yes

pluggable indexing subsystem, by default Apache Lucene

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

.Net
JDBC
ODBC
WebSocket

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

.Net

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

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

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

.Net

Server-side scripts

Stored procedures

Lua

user defined functions

yes

User defined Procedures and Functions

Triggers

publish/subscribe channels provide some trigger functionality

yes

via event handler

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes using Neo4j Fabric

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Causal Clustering using Raft protocol

available in in Enterprise Version only

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

via file-system locks

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

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

Based on Windows Authentication

More information provided by the system vendor

Specific characteristics

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Key customers

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Market metrics

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Licensing and pricing models

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