DBMS > Dgraph vs. EsgynDB vs. GeoMesa vs. Google Cloud Firestore vs. HyperSQL

System Properties Comparison Dgraph vs. EsgynDB vs. GeoMesa vs. Google Cloud Firestore vs. HyperSQL

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Primary database model

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	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Website

dgraph.io

www.esgyn.cn

www.geomesa.org

firebase.google.com/products/firestore

hsqldb.org

Technical documentation

dgraph.io/docs

www.geomesa.org/documentation/stable/user/index.html

firebase.google.com/docs/firestore

hsqldb.org/web/hsqlDocsFrame.html

Developer

Dgraph Labs, Inc.

Esgyn

CCRi and others

Google

Initial release

2016

2015

2014

2017

2001

Current release

5.0.0, May 2024

2.7.2, June 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache License 2.0

commercial

Open Source

based on BSD license

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

Scala

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

Data scheme

schema-free

yes

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

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

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

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

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes, Firebase Rules & Cloud Functions

Java, SQL

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

depending on storage layer

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication between multi datacenters

depending on storage layer

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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.

depending on storage layer

yes

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

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

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

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

show all

Recent citations in the news

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

Dgraph Raises $6M in Seed Funding
20 July 2022, FinSMEs

Dgraph Rises to the Top Graph Database on GitHub With 11 G2 Badges and 11M Downloads
26 May 2021, Business Wire

Dgraph launches Slash GraphQL, a GraphQL-native database Backend-as-a-Service
10 September 2020, TechCrunch

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14 May 2024, Yahoo Canada Finance

Google's Cloud Firestore is now generally available
31 January 2019, ZDNet

Google launches Cloud Firestore, a new document database for app developers
3 October 2017, TechCrunch

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Introduction to JDBC with HSQLDB tutorial
14 November 2022, TheServerSide.com

HyperSQL DataBase flaw leaves library vulnerable to RCE
24 October 2022, The Daily Swig

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