DBMS > Dgraph vs. EsgynDB vs. Firebird vs. Hive

System Properties Comparison Dgraph vs. EsgynDB vs. Firebird vs. Hive

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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

Firebird is an open source RDBMS forked from Borland's InterBase

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Primary database model

Graph DBMS

Relational DBMS

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Website

Technical documentation

dgraph.io/docs

www.firebirdsql.org/en/reference-manuals

cwiki.apache.org/confluence/display/Hive/Home

Developer

Dgraph Labs, Inc.

Esgyn

Firebird Foundation

Apache Software Foundation

initially developed by Facebook

Initial release

2016

2015

2000

As fork of Borland's InterBase

2012

Current release

5.0.0, January 2024

3.1.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Initial Developer's Public License

Open Source

Apache Version 2

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.

Implementation language

C++, Java

C and C++

Java

Server operating systems

Linux
OS X
Windows

Linux

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

All OS with a Java VM

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

SQL-like DML and DDL statements

APIs and other access methods

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

ADO.NET
JDBC
ODBC

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
ODBC
Thrift

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C++
Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

PSQL

yes

user defined functions and integration of map-reduce

Triggers

yes

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

Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

Features a multi-generational MVCC architecture, readers do not block writers

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.

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

Access rights for users, groups and roles

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More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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