DBMS > Google BigQuery vs. MaxDB vs. Microsoft Azure Synapse Analytics vs. MySQL vs. STSdb

System Properties Comparison Google BigQuery vs. MaxDB vs. Microsoft Azure Synapse Analytics vs. MySQL vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A robust and reliable RDBMS optimized to run all major SAP solutions

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Widely used open source RDBMS

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Key/Value like access via memcached API

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

cloud.google.com/bigquery

maxdb.sap.com

azure.microsoft.com/services/synapse-analytics

www.mysql.com

github.com/STSSoft/STSdb4

Technical documentation

cloud.google.com/bigquery/docs

maxdb.sap.com/documentation

docs.microsoft.com/azure/synapse-analytics

dev.mysql.com/doc

Developer

Google

SAP, acquired from Software AG (Adabas-D) in 1997

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

STS Soft SC

Initial release

2010

1984

2016

1995

2011

Current release

7.9.10.12, February 2024

8.4.0, April 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

Limited community edition free

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPLv2, commercial license 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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C++

C and C++

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
WebDAV

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C#
Java
Perl
PHP
Python

C#
Java
PHP

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

C#
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Transact SQL

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

not for MyISAM storage engine

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

not for MyISAM storage engine

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

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

yes

Users with fine-grained authorization concept

no user groups or roles

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.