DBMS > Google BigQuery vs. mSQL vs. Postgres-XL vs. SwayDB

System Properties Comparison Google BigQuery vs. mSQL vs. Postgres-XL vs. SwayDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

mSQL (Mini SQL) is a simple and lightweight RDBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	1.67
Rank	#151	Overall
	#70	Relational DBMS

Score	0.52
Rank	#256	Overall
	#117	Relational DBMS

Score	0.04
Rank	#373	Overall
	#57	Key-value stores

Website

cloud.google.com/bigquery

hughestech.com.au/products/msql

www.postgres-xl.org

swaydb.simer.au

Technical documentation

cloud.google.com/bigquery/docs

www.postgres-xl.org/documentation

Developer

Google

Hughes Technologies

Simer Plaha

Initial release

2010

1994

2014

since 2012, originally named StormDB

2018

Current release

4.4, October 2021

10 R1, October 2018

License

Commercial or Open Source

commercial

free licenses can be provided

Open Source

Mozilla public license

Open Source

GNU Affero GPL V3.0

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

Scala

Server operating systems

hosted

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

Linux
macOS

Data scheme

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

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

yes

distributed, parallel query execution

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

in JavaScript

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

MVCC

Atomic execution of operations

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.