DBMS > EsgynDB vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. JSqlDb vs. Kingbase

System Properties Comparison EsgynDB vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. JSqlDb vs. Kingbase

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

JavaScript Query Language Database, stores JavaScript objects and primitives

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Primary database model

Relational DBMS

Document store

Key-value store
Wide column store

Document store
Object oriented DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Score	0.44
Rank	#258	Overall
	#117	Relational DBMS

Website

www.esgyn.cn

firebase.google.com/products/realtime-database

cloud.google.com/bigtable

jsqldb.org (offline)

www.kingbase.com.cn

Technical documentation

firebase.google.com/docs/database

cloud.google.com/bigtable/docs

Developer

Esgyn

Google

acquired by Google 2014

Google

Konrad von Backstrom

BeiJing KINGBASE Information technologies inc.

Initial release

2015

2012

2015

2018

1999

Current release

0.8, December 2018

V8.0, August 2021

License

Commercial or Open Source

commercial

Open Source

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++, Java

C and Java

Server operating systems

Linux

hosted

Linux
macOS
Windows

Linux
Windows

Data scheme

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

ADO.NET
JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript
Objective-C

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

JavaScript

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

Server-side scripts

Stored procedures

Java Stored Procedures

limited functionality with using 'rules'

functions in JavaScript

user defined functions

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Internal replication in Colossus, and regional replication between two clusters in different zones

none

yes

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 (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

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

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