DBMS > EsgynDB vs. Google Cloud Firestore vs. Lovefield vs. MySQL vs. SurrealDB

System Properties Comparison EsgynDB vs. Google Cloud Firestore vs. Lovefield vs. MySQL vs. SurrealDB

Editorial information provided by DB-Engines

Name

Description

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

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Embeddable relational database for web apps written in pure JavaScript

Widely used open source RDBMS

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Relational DBMS

Document store

Relational DBMS

Key/Value like access via memcached API

Document store
Graph 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	6.63
Rank	#54	Overall
	#9	Document stores

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	1.11
Rank	#174	Overall
	#30	Document stores
	#17	Graph DBMS

Website

www.esgyn.cn

firebase.google.com/products/firestore

google.github.io/lovefield

www.mysql.com

surrealdb.com

Technical documentation

firebase.google.com/docs/firestore

github.com/google/lovefield/blob/master/docs/spec_index.md

dev.mysql.com/doc

surrealdb.com/docs

Developer

Esgyn

Google

Oracle

since 2010, originally MySQL AB, then Sun

SurrealDB Ltd

Initial release

2015

2017

2014

1995

2022

Current release

2.1.12, February 2017

9.0.0, July 2024

v1.5.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

JavaScript

C and C++

Rust

Server operating systems

Linux

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

JavaScript

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

Java Stored Procedures

yes, Firebase Rules & Cloud Functions

yes

proprietary syntax

Triggers

yes, with Cloud Functions

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Multi-source replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

yes

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Users with fine-grained authorization concept

no user groups or roles

yes, based on authentication and database rules

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