DBMS > Dgraph vs. EJDB vs. Firebird vs. JanusGraph vs. Microsoft Azure Cosmos DB

System Properties Comparison Dgraph vs. EJDB vs. Firebird vs. JanusGraph vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

dgraph.io

github.com/Softmotions/ejdb

www.firebirdsql.org

janusgraph.org

azure.microsoft.com/services/cosmos-db

Technical documentation

dgraph.io/docs

github.com/Softmotions/ejdb/blob/master/README.md

www.firebirdsql.org/en/reference-manuals

docs.janusgraph.org

learn.microsoft.com/azure/cosmos-db

Developer

Dgraph Labs, Inc.

Softmotions

Firebird Foundation

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

Initial release

2016

2012

2000

As fork of Borland's InterBase

2017

2014

Current release

5.0.0, January 2024

0.6.3, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2

Open Source

Initial Developer's Public License

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

Java

Server operating systems

Linux
OS X
Windows

server-less

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
OS X
Unix
Windows

hosted

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

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

in-process shared library

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

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

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

Clojure
Java
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

PSQL

yes

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

yes

none

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

none

Source-replica replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Relationships in graphs

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

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

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

User concepts

Access control

Planned for future releases

Users with fine-grained authorization concept

User authentification and security via Rexster Graph Server

Access rights can be defined down to the item level

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