DBMS > Google BigQuery vs. Microsoft Azure Synapse Analytics vs. MonetDB vs. OpenQM vs. TempoIQ

System Properties Comparison Google BigQuery vs. Microsoft Azure Synapse Analytics vs. MonetDB vs. OpenQM vs. TempoIQ

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

Large scale data warehouse service with append-only tables

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

A relational database management system that stores data in columns

QpenQM is a high-performance, self-tuning, multi-value DBMS

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Relational DBMS

Multivalue DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Website

cloud.google.com/bigquery

azure.microsoft.com/services/synapse-analytics

www.monetdb.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

tempoiq.com (offline)

Technical documentation

cloud.google.com/bigquery/docs

docs.microsoft.com/azure/synapse-analytics

www.monetdb.org/Documentation

Developer

Google

Microsoft

MonetDB BV

Rocket Software, originally Martin Phillips

TempoIQ

Initial release

2010

2016

2004

1993

2012

Current release

Dec2023 (11.49), December 2023

3.4-12

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

GPLv2, extended commercial license 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++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

with some exceptions

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
PHP

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

.Net
Basic
C
Java
Objective C
PHP
Python

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Transact SQL

yes, in SQL, C, R

yes

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

Sharding via remote tables

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication available in experimental status

yes

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

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

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

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)

yes

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

simple authentication-based access control

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