DBMS > Firebolt vs. Google BigQuery vs. IBM Db2 warehouse vs. Microsoft Access

System Properties Comparison Firebolt vs. Google BigQuery vs. IBM Db2 warehouse vs. Microsoft Access

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Editorial information provided by DB-Engines

Name

Description

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Large scale data warehouse service with append-only tables

Cloud-based data warehousing service

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Primary database model

Relational DBMS

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Trend Chart

Score	1.49
Rank	#148	Overall
	#68	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	1.26
Rank	#162	Overall
	#73	Relational DBMS

Score	93.76
Rank	#12	Overall
	#8	Relational DBMS

Website

www.firebolt.io

cloud.google.com/bigquery

www.ibm.com/products/db2/warehouse

www.microsoft.com/en-us/microsoft-365/access

Technical documentation

docs.firebolt.io

cloud.google.com/bigquery/docs

developer.microsoft.com/en-us/access

Developer

Firebolt Analytics Inc.

Google

IBM

Microsoft

Initial release

2020

2010

2014

1992

Current release

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

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

Windows

Not a real database server, but making use of DLLs

Data scheme

yes

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.

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

APIs and other access methods

.Net
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
OLE DB

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

Go
JavaScript (Node.js)
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

in JavaScript

PL/SQL, SQL PL

yes

since Access 2010 using the ACE-engine

Triggers

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

none

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

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

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)

fine grained access rights according to SQL-standard

a simple user-level security was built in till version Access 2003

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