DBMS > Google BigQuery vs. mSQL vs. OpenQM vs. VictoriaMetrics vs. YDB

System Properties Comparison Google BigQuery vs. mSQL vs. OpenQM vs. VictoriaMetrics vs. YDB

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

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

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Multivalue DBMS

Time Series DBMS

Document store
Relational DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Score	0.35
Rank	#278	Overall
	#43	Document stores
	#127	Relational DBMS

Website

cloud.google.com/bigquery

hughestech.com.au/products/msql

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

victoriametrics.com

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

cloud.google.com/bigquery/docs

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

ydb.tech/en/docs

Developer

Google

Hughes Technologies

Rocket Software, originally Martin Phillips

VictoriaMetrics

Yandex

Initial release

2010

1994

1993

2018

2019

Current release

4.4, October 2021

3.4-12

v1.91, May 2023

License

Commercial or Open Source

commercial

free licenses can be provided

Open Source

GPLv2, extended commercial license available

Open Source

Apache Version 2.0

Open Source

Apache 2.0; 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.

Implementation language

Server operating systems

hosted

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

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

FreeBSD
Linux
macOS
OpenBSD

Linux

Data scheme

yes

with some exceptions

Flexible Schema (defined schema, partial schema, 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

A subset of ANSI SQL is implemented

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

SQL-like query language (YQL)

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net
Basic
C
Java
Objective C
PHP
Python

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Synchronous replication

Active-passive shard replication

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

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)

Access rights can be defined down to the item level

Access rights defined for Yandex Cloud users

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