DBMS > Google BigQuery vs. Kyligence Enterprise vs. Microsoft Access vs. PostGIS

System Properties Comparison Google BigQuery vs. Kyligence Enterprise vs. Microsoft Access vs. PostGIS

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A distributed analytics engine for big data, built on top of Apache Kylin

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.)

Spatial extension of PostgreSQL

Primary database model

Relational DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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Trend Chart

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Website

cloud.google.com/bigquery

kyligence.io/kyligence-enterprise

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

postgis.net

Technical documentation

cloud.google.com/bigquery/docs

developer.microsoft.com/en-us/access

postgis.net/documentation

Developer

Google

Kyligence, Inc.

Microsoft

Initial release

2010

2016

1992

2005

Current release

1902 (16.0.11328.20222), March 2019

3.4.2, February 2024

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

Open Source

GPL v2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

hosted

Linux

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL for queries (using Apache Calcite)

yes

but not compliant to any SQL standard

yes

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

since Access 2010 using the ACE-engine

user defined functions

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

based on PostgreSQL

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

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)

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

yes

based on PostgreSQL

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