DBMS > Google BigQuery vs. InfluxDB vs. Ingres vs. Interbase vs. mSQL

System Properties Comparison Google BigQuery vs. InfluxDB vs. Ingres vs. Interbase vs. mSQL

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

Well established RDBMS

Light-weight proven RDBMS

originally from Borland

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Website

cloud.google.com/bigquery

www.influxdata.com/products/influxdb-overview

www.actian.com/databases/ingres

www.embarcadero.com/products/interbase

hughestech.com.au/products/msql

Technical documentation

cloud.google.com/bigquery/docs

docs.influxdata.com/influxdb

docs.actian.com/ingres

docs.embarcadero.com/products/interbase

Developer

Google

Actian Corporation

Embarcadero

Hughes Technologies

Initial release

2010

2013

1974

originally developed at University Berkely in early 1970s

1984

1994

Current release

2.7.6, April 2024

11.2, May 2022

InterBase 2020, December 2019

4.4, October 2021

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

commercial

free licenses can be provided

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

Linux
OS X

through Homebrew

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Android
iOS
Linux
OS X
Windows

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

Data scheme

yes

schema-free

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.

but tools for importing/exporting data from/to XML-files available

export as XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

A subset of ANSI SQL is implemented

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

APIs and other access methods

RESTful HTTP/JSON API

HTTP API
JSON over UDP

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
ODBC

JDBC
ODBC

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
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Interbase procedure and trigger language

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

in enterprise version only

horizontal partitioning

Ingres Star to access multiple databases simultaneously

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

in enterprise version only

Ingres Replicator

Interbase Change Views

none

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

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Multiversion concurreny control

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

yes

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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