DBMS > Dgraph vs. Fujitsu Enterprise Postgres vs. Google Cloud Firestore

System Properties Comparison Dgraph vs. Fujitsu Enterprise Postgres vs. Google Cloud Firestore

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Primary database model

Graph DBMS

Relational DBMS

Document store

Secondary database models

Document store
Spatial DBMS

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

Score	1.39
Rank	#155	Overall
	#15	Graph DBMS

Score	0.22
Rank	#304	Overall
	#137	Relational DBMS

Score	6.63
Rank	#54	Overall
	#9	Document stores

Website

dgraph.io

www.postgresql.fastware.com

firebase.google.com/products/firestore

Technical documentation

dgraph.io/docs

www.postgresql.fastware.com/product-manuals

firebase.google.com/docs/firestore

Developer

Dgraph Labs, Inc.

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Google

Initial release

2016

2017

Current release

Fujitsu Enterprise Postgres 14, January 2022

License

Commercial or Open Source

Open Source

Apache 2.0

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

Server operating systems

Linux
OS X
Windows

Linux
Windows

hosted

Data scheme

schema-free

yes

schema-free

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
native C library
ODBC
streaming API for large objects

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

Supported programming languages

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

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

Server-side scripts

Stored procedures

user defined functions

yes, Firebase Rules & Cloud Functions

Triggers

yes

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

yes

partitioning by range, list and by hash

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

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

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

show all

Recent citations in the news

Top Open Source Graph Databases
3 June 2024, MarkTechPost

Graph Database Market size to grow by USD 7.40 billion between 2022 - 2027 | Growth Driven by Lack of standardization and programming flexibility - Technavio
13 December 2023, Yahoo Finance

Dgraph on AWS: Setting up a horizontally scalable graph database
1 September 2020, AWS Blog

Dgraph raises $11.5 million for scalable graph database solutions
31 July 2019, VentureBeat

provided by Google News

Fujitsu Develops Database Integration Technology to Accelerate IoT Data Analysis
17 March 2017, Fujitsu

Fujitsu recognized as winner of 2023 Microsoft Japan Healthcare & Life Sciences Partner of the Year Award for its cloud-based platform for healthcare sector
28 June 2023, Fujitsu

Intel® Optane™ DC Persistent Memory & FUJITSU Server PRIMERGY
1 August 2020, Fujitsu

Linux on IBM Z and LinuxONE: The Ecosystem of Choice for Hybrid Cloud
17 September 2020, IBM Newsroom

Red Hat OpenShift’s great momentum on IBM Z and LinuxONE
4 August 2021, IBM

provided by Google News

Realtime vs Cloud Firestore: Which Firebase Database to Choose
8 March 2024, Appinventiv

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google launches Firebase Genkit, a new open source framework for building AI-powered apps
14 May 2024, TechCrunch

NoSQL on the Cloud With Python
7 August 2020, Towards Data Science

Spring Boot Tutorial: Building Microservices Deployed to Google Cloud
26 March 2020, InfoQ.com

provided by Google News

Share this page