DBMS > Google Cloud Datastore vs. Microsoft Access vs. Microsoft SQL Server vs. Percona Server for MySQL

System Properties Comparison Google Cloud Datastore vs. Microsoft Access vs. Microsoft SQL Server vs. Percona Server for MySQL

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Editorial information provided by DB-Engines

Name

Description

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

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.)

Microsofts flagship relational DBMS

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

Primary database model

Document store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	4.13
Rank	#71	Overall
	#12	Document stores

Score	93.76
Rank	#12	Overall
	#8	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	2.06
Rank	#118	Overall
	#57	Relational DBMS

Website

cloud.google.com/datastore

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

www.microsoft.com/en-us/sql-server

www.percona.com/software/mysql-database/percona-server

Technical documentation

cloud.google.com/datastore/docs

developer.microsoft.com/en-us/access

learn.microsoft.com/en-US/sql/sql-server

www.percona.com/downloads/Percona-Server-LATEST

Developer

Google

Microsoft

Percona

Initial release

2008

1992

1989

2008

Current release

1902 (16.0.11328.20222), March 2019

SQL Server 2022, November 2022

8.0.36-28, 2024

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

commercial

restricted free version is available

Open Source

GPL version 2

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

C and C++

Server operating systems

hosted

Windows

Not a real database server, but making use of DLLs

Linux
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes, details here

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

SQL-like query language (GQL)

yes

but not compliant to any SQL standard

yes

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

using Google App Engine

yes

since Access 2010 using the ACE-engine

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

Callbacks using the Google Apps Engine

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

none

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication
XtraDB Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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.

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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