DBMS > Geode vs. Google Cloud Datastore vs. H2GIS vs. Microsoft Access vs. MySQL

System Properties Comparison Geode vs. Google Cloud Datastore vs. H2GIS vs. Microsoft Access vs. MySQL

Editorial information provided by DB-Engines

Name

Description

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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

Spatial extension of H2

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

Primary database model

Key/Value like access via memcached API

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

geode.apache.org

cloud.google.com/datastore

www.h2gis.org

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

www.mysql.com

Technical documentation

geode.apache.org/docs

cloud.google.com/datastore/docs

www.h2gis.org/docs/home

developer.microsoft.com/en-us/access

dev.mysql.com/doc

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Google

CNRS

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2002

2008

2013

1992

1995

Current release

1.1, February 2017

1902 (16.0.11328.20222), March 2019

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

LGPL 3.0

commercial

Bundled with Microsoft Office

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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++

C and C++

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

hosted

Windows

Not a real database server, but making use of DLLs

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

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 (OQL)

SQL-like query language (GQL)

yes

but not compliant to any SQL standard

yes

with proprietary extensions

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

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

ADO.NET
DAO
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

.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

Server-side scripts

Stored procedures

user defined functions

using Google App Engine

yes

based on H2

yes

since Access 2010 using the ACE-engine

yes

proprietary syntax

Triggers

yes

Cache Event Listeners

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication using Paxos

yes

based on H2

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

Eventual Consistency

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

yes, on a single node

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

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 per client and object definable

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

yes

based on H2

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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