DBMS > EsgynDB vs. Firebase Realtime Database vs. TDSQL for MySQL vs. TerarkDB

System Properties Comparison EsgynDB vs. Firebase Realtime Database vs. TDSQL for MySQL vs. TerarkDB

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Editorial information provided by DB-Engines

Name

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.

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.85
Rank	#205	Overall
	#95	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.esgyn.cn

firebase.google.com/products/realtime-database

www.tencentcloud.com/products/dcdb

github.com/bytedance/terarkdb

Technical documentation

firebase.google.com/docs/database

www.tencentcloud.com/document/product/1042

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Esgyn

Google

acquired by Google 2014

Tencent

ByteDance, originally Terark

Initial release

2015

2012

2013

2016

License

Commercial or Open Source

commercial

restricted open source version available

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++

Server operating systems

Linux

hosted

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

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript
Objective-C

C
C#
C++
Java
PHP
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

Java Stored Procedures

limited functionality with using 'rules'

yes

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Multi-source replication
Source-replica replication

none

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

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

Users with fine-grained authorization concept

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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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