DBMS > EsgynDB vs. EXASOL vs. Firebase Realtime Database vs. HyperSQL vs. SwayDB

System Properties Comparison EsgynDB vs. EXASOL vs. Firebase Realtime Database vs. HyperSQL vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

www.esgyn.cn

www.exasol.com

firebase.google.com/products/realtime-database

hsqldb.org

swaydb.simer.au

Technical documentation

www.exasol.com/resources

firebase.google.com/docs/database

hsqldb.org/web/hsqlDocsFrame.html

Developer

Esgyn

Exasol

Google

acquired by Google 2014

Simer Plaha

Initial release

2015

2000

2012

2001

2018

Current release

2.7.2, June 2023

License

Commercial or Open Source

commercial

Open Source

based on BSD license

Open Source

GNU Affero GPL V3.0

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

Scala

Server operating systems

Linux

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Data scheme

yes

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

ADO.NET
JDBC
ODBC

.Net
JDBC
ODBC
WebSocket

Android
iOS
JavaScript API
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java
Lua
Python
R

Java
JavaScript
Objective-C

All languages supporting JDBC/ODBC
Java

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

limited functionality with using 'rules'

Java, SQL

Triggers

yes

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

Transaction concepts

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

ACID

yes

ACID

Atomic execution of operations

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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