DBMS > Google Cloud Bigtable vs. mSQL vs. MySQL vs. RDFox vs. SQL.JS

System Properties Comparison Google Cloud Bigtable vs. mSQL vs. MySQL vs. RDFox vs. SQL.JS

Editorial information provided by DB-Engines

Name

Description

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used open source RDBMS

High performance knowledge graph and semantic reasoning engine

Port of SQLite to JavaScript

Primary database model

Key-value store
Wide column store

Relational DBMS

Key/Value like access via memcached API

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

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

Score	1.26
Rank	#163	Overall
	#74	Relational DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	0.22
Rank	#305	Overall
	#25	Graph DBMS
	#15	RDF stores

Score	0.53
Rank	#246	Overall
	#115	Relational DBMS

Website

cloud.google.com/bigtable

hughestech.com.au/products/msql

www.mysql.com

www.oxfordsemantic.tech

sql.js.org

Technical documentation

cloud.google.com/bigtable/docs

dev.mysql.com/doc

docs.oxfordsemantic.tech

sql.js.org/documentation/index.html

Developer

Google

Hughes Technologies

Oracle

since 2010, originally MySQL AB, then Sun

Oxford Semantic Technologies

Alon Zakai

enhancements implemented by others

Initial release

2015

1994

1995

2017

2012

Current release

4.4, October 2021

9.0.0, July 2024

6.0, Septermber 2022

License

Commercial or Open Source

commercial

free licenses can be provided

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

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++

JavaScript

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

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

Data scheme

schema-free

yes

RDF schemas

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

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

with proprietary extensions

yes

SQL-92 is not fully supported

APIs and other access methods

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

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP API
SPARQL 1.1

JavaScript API

Supported programming languages

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

C
C++
Delphi
Java
Perl
PHP
Tcl

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

C
Java

JavaScript

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Multi-source replication
Source-replica replication

replication via a shared file system

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

none

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

none

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

Atomic single-row operations

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

except by serializing a db to a file

In-memory capabilities

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

yes

User concepts

Access control

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

Users with fine-grained authorization concept

no user groups or roles

Roles, resources, and access types

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