DBMS > Google Cloud Datastore vs. Microsoft Access vs. SQLite vs. TDSQL for MySQL

System Properties Comparison Google Cloud Datastore vs. Microsoft Access vs. SQLite vs. TDSQL 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.)

Widely used embeddable, in-process RDBMS

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Document store

Relational DBMS

Secondary database models

Document store
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	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	0.96
Rank	#192	Overall
	#88	Relational DBMS

Website

cloud.google.com/datastore

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

www.sqlite.org

www.tencentcloud.com/products/dcdb

Technical documentation

cloud.google.com/datastore/docs

developer.microsoft.com/en-us/access

www.sqlite.org/docs.html

www.tencentcloud.com/document/product/1042

Developer

Google

Microsoft

Dwayne Richard Hipp

Tencent

Initial release

2008

1992

2000

2013

Current release

1902 (16.0.11328.20222), March 2019

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

Open Source

Public Domain

commercial

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

server-less

hosted

Data scheme

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes, details here

yes

not rigid because of 'dynamic typing' concept.

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

SQL-like query language (GQL)

yes

but not compliant to any SQL standard

yes

SQL-92 is not fully supported

yes

APIs and other access methods

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

ADO.NET
DAO
ODBC
OLE DB

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

using Google App Engine

yes

since Access 2010 using the ACE-engine

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

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

none

Multi-source replication
Source-replica replication

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

via file-system locks

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

Users with fine-grained authorization concept

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