DBMS > Google BigQuery vs. Microsoft Access vs. Oracle Coherence

System Properties Comparison Google BigQuery vs. Microsoft Access vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

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.)

Oracles in-memory data grid solution

Primary database model

Relational DBMS

Key-value store

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Score	60.38
Rank	#19	Overall
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Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

cloud.google.com/bigquery

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

www.oracle.com/java/coherence

Technical documentation

cloud.google.com/bigquery/docs

developer.microsoft.com/en-us/access

docs.oracle.com/en/middleware/standalone/coherence

Developer

Google

Microsoft

Oracle

Initial release

2010

1992

2007

Current release

1902 (16.0.11328.20222), March 2019

14.1, August 2023

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

hosted

Windows

Not a real database server, but making use of DLLs

All OS with a Java VM

Data scheme

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

JCache
JPA
RESTful HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

.Net
C++
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

since Access 2010 using the ACE-engine

Triggers

yes

since Access 2010 using the ACE-engine

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
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

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

optionally

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)

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

authentification to access the cache via certificates or http basic authentication

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