DBMS > AgensGraph vs. EsgynDB vs. Firebase Realtime Database vs. H2GIS vs. VoltDB

System Properties Comparison AgensGraph vs. EsgynDB vs. Firebase Realtime Database vs. H2GIS vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Spatial extension of H2

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Graph DBMS
Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

bitnine.net/agensgraph

www.esgyn.cn

firebase.google.com/products/realtime-database

www.h2gis.org

www.voltdb.com

Technical documentation

bitnine.net/documentation

firebase.google.com/docs/database

www.h2gis.org/docs/home

docs.voltdb.com

Developer

Bitnine Global Inc.

Esgyn

Google

acquired by Google 2014

CNRS

VoltDB Inc.

Initial release

2016

2015

2012

2013

2010

Current release

2.1, December 2018

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

LGPL 3.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java, C++

Server operating systems

Linux
OS X
Windows

Linux

hosted

Linux
OS X

for development

Data scheme

depending on used data model

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

only a subset of SQL 99

APIs and other access methods

Cypher Query Language
JDBC

ADO.NET
JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C
Java
JavaScript
Python

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript
Objective-C

Java

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Java Stored Procedures

limited functionality with using 'rules'

yes

based on H2

Java

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication between multi datacenters

yes

based on H2

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

yes

based on H2

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
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