DBMS > Google BigQuery vs. MySQL vs. Prometheus vs. Yanza

System Properties Comparison Google BigQuery vs. MySQL vs. Prometheus vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Large scale data warehouse service with append-only tables

Widely used open source RDBMS

Open-source Time Series DBMS and monitoring system

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

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	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Website

cloud.google.com/bigquery

www.mysql.com

prometheus.io

yanza.com

Technical documentation

cloud.google.com/bigquery/docs

dev.mysql.com/doc

prometheus.io/docs

Developer

Google

Oracle

since 2010, originally MySQL AB, then Sun

Yanza

Initial release

2010

1995

2015

Current release

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

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Implementation language

C and C++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Windows

Data scheme

yes

schema-free

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

with proprietary extensions

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP/JSON API

HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

proprietary syntax

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

by Federation

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

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)

Users with fine-grained authorization concept

no user groups or roles

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