DBMS > Amazon Neptune vs. Google Cloud Firestore vs. MySQL vs. Tibero

System Properties Comparison Amazon Neptune vs. Google Cloud Firestore vs. MySQL vs. Tibero

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

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.

Widely used open source RDBMS

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Graph DBMS
RDF store

Document store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.20
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	6.63
Rank	#54	Overall
	#9	Document stores

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	1.46
Rank	#151	Overall
	#70	Relational DBMS

Website

aws.amazon.com/neptune

firebase.google.com/products/firestore

www.mysql.com

us.tmaxsoft.com/products/tibero

Technical documentation

aws.amazon.com/neptune/developer-resources

firebase.google.com/docs/firestore

dev.mysql.com/doc

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Amazon

Google

Oracle

since 2010, originally MySQL AB, then Sun

TmaxSoft

Initial release

2017

1995

2003

Current release

9.0.0, July 2024

7, September 2022

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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 and C++

C and Assembler

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

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

with proprietary extensions

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

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

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

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

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

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

proprietary syntax

Persistent Stored Procedure (PSM)

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

not for MyISAM storage engine

yes

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

with encyption-at-rest

yes

In-memory capabilities

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

yes

planned for next version

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

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

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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