DBMS > Dgraph vs. EsgynDB vs. Firebolt vs. HyperSQL vs. VelocityDB

System Properties Comparison Dgraph vs. EsgynDB vs. Firebolt vs. HyperSQL vs. VelocityDB

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

Primary database model

Graph DBMS

Relational DBMS

Graph DBMS
Object oriented DBMS

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	1.73
Rank	#140	Overall
	#63	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

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

Website

Technical documentation

dgraph.io/docs

docs.firebolt.io

hsqldb.org/web/hsqlDocsFrame.html

velocitydb.com/UserGuide

Developer

Dgraph Labs, Inc.

Esgyn

Firebolt Analytics Inc.

VelocityDB Inc

Initial release

2016

2015

2020

2001

2011

Current release

2.7.2, June 2023

7.x

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

based on BSD license

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++, Java

Java

Server operating systems

Linux
OS X
Windows

Linux

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Any that supports .NET

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

ADO.NET
JDBC
ODBC

.Net
ODBC
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

.Net

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

Go
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC
Java

.Net

Server-side scripts

Stored procedures

Java Stored Procedures

Java, SQL

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication between multi datacenters

depending on storage layer

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

Planned for future releases

fine grained access rights according to SQL-standard

Based on Windows Authentication

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More resources

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