DBMS > Google BigQuery vs. Microsoft Azure SQL Database vs. Oracle Rdb vs. Prometheus

System Properties Comparison Google BigQuery vs. Microsoft Azure SQL Database vs. Oracle Rdb vs. Prometheus

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

Database as a Service offering with high compatibility to Microsoft SQL Server

Open-source Time Series DBMS and monitoring system

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Website

cloud.google.com/bigquery

azure.microsoft.com/en-us/products/azure-sql/database

www.oracle.com/database/technologies/related/rdb.html

prometheus.io

Technical documentation

cloud.google.com/bigquery/docs

docs.microsoft.com/en-us/azure/azure-sql

www.oracle.com/database/technologies/related/rdb-doc.html

prometheus.io/docs

Developer

Google

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2010

1984

2015

Current release

V12

7.4.1.1, 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

C++

Server operating systems

hosted

HP Open VMS

Linux
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

RESTful HTTP/JSON API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with always 3 replicas available

yes

by Federation

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

yes, on a single node

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.

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.