DBMS > Cachelot.io vs. EsgynDB vs. Firebase Realtime Database vs. GBase

System Properties Comparison Cachelot.io vs. EsgynDB vs. Firebase Realtime Database vs. GBase

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Editorial information provided by DB-Engines

Name

Description

In-memory caching system

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.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Primary database model

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

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Website

cachelot.io

www.esgyn.cn

firebase.google.com/products/realtime-database

www.gbase.cn

Technical documentation

firebase.google.com/docs/database

Developer

Esgyn

Google

acquired by Google 2014

General Data Technology Co., Ltd.

Initial release

2015

2012

2004

Current release

GBase 8a, GBase 8s, GBase 8c

License

Commercial or Open Source

Open Source

Simplified BSD License

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

C++

C++, Java

C, Java, Python

Server operating systems

FreeBSD
Linux
OS X

Linux

hosted

Linux

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

Standard with numerous extensions

APIs and other access methods

Memcached protocol

ADO.NET
JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript
Objective-C

Server-side scripts

Stored procedures

Java Stored Procedures

limited functionality with using 'rules'

user defined functions

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

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.

User concepts

Access control

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

yes

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More resources

DB-Engines blog posts

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12 December 2019, Paul Andlinger

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