DBMS > Google Cloud Datastore vs. H2 vs. Microsoft Access vs. MySQL vs. Yanza

System Properties Comparison Google Cloud Datastore vs. H2 vs. Microsoft Access vs. MySQL vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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 open source RDBMS

Time Series DBMS for IoT Applications

Primary database model

Document store

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

cloud.google.com/datastore

www.h2database.com

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

www.mysql.com

yanza.com

Technical documentation

cloud.google.com/datastore/docs

www.h2database.com/html/main.html

developer.microsoft.com/en-us/access

dev.mysql.com/doc

Developer

Google

Thomas Mueller

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Yanza

Initial release

2008

2005

1992

1995

2015

Current release

2.2.220, July 2023

1902 (16.0.11328.20222), March 2019

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Bundled with Microsoft Office

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

Java

C++

C and C++

Server operating systems

hosted

All OS with a Java VM

Windows

Not a real database server, but making use of DLLs

FreeBSD
Linux
OS X
Solaris
Windows

Windows

Data scheme

schema-free

yes

schema-free

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

with proprietary extensions

APIs and other access methods

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

JDBC
ODBC

ADO.NET
DAO
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API

Supported programming languages

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

Java

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

any language that supports HTTP calls

Server-side scripts

Stored procedures

using Google App Engine

Java Stored Procedures and User-Defined Functions

yes

since Access 2010 using the ACE-engine

yes

proprietary syntax

Triggers

Callbacks using the Google Apps Engine

yes

since Access 2010 using the ACE-engine

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

With clustering: 2 database servers on different computers operate on identical copies of a database

none

Multi-source replication
Source-replica replication

none

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

not for MyISAM storage engine

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

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

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)

fine grained access rights according to SQL-standard

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

Users with fine-grained authorization concept

no user groups or roles

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