DBMS > Google BigQuery vs. InfluxDB vs. OpenQM vs. Tibero

System Properties Comparison Google BigQuery vs. InfluxDB vs. OpenQM vs. Tibero

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

DBMS for storing time series, events and metrics

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

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Secondary database models

Spatial DBMS

with GEO package

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

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	26.56
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.33
Rank	#286	Overall
	#10	Multivalue DBMS

Score	1.81
Rank	#143	Overall
	#65	Relational DBMS

Website

cloud.google.com/bigquery

www.influxdata.com/products/influxdb-overview

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

us.tmaxsoft.com/products/tibero

Technical documentation

cloud.google.com/bigquery/docs

docs.influxdata.com/influxdb

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Google

Rocket Software, originally Martin Phillips

TmaxSoft

Initial release

2010

2013

1993

2003

Current release

2.7.5, January 2024

3.4-12

6, April 2015

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

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 and Assembler

Server operating systems

hosted

Linux
OS X

through Homebrew

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

yes

with some exceptions

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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-like query language

yes

APIs and other access methods

RESTful HTTP/JSON API

HTTP API
JSON over UDP

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Persistent Stored Procedure (PSM)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

in enterprise version only

yes

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

in enterprise version only

yes

Multi-source replication
Source-replica replication

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

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.

yes

Depending on used storage engine

planned for next version

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

simple rights management via user accounts

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

More information provided by the system vendor

Specific characteristics

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Key customers

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Market metrics

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Licensing and pricing models

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