DBMS > Amazon DocumentDB vs. GeoMesa vs. Microsoft Access vs. Microsoft Azure Cosmos DB vs. SiteWhere

System Properties Comparison Amazon DocumentDB vs. GeoMesa vs. Microsoft Access vs. Microsoft Azure Cosmos DB vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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.)

Globally distributed, horizontally scalable, multi-model database service

M2M integration platform for persisting/querying time series data

Primary database model

Document store

Spatial DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

aws.amazon.com/documentdb

www.geomesa.org

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

azure.microsoft.com/services/cosmos-db

github.com/sitewhere/sitewhere

Technical documentation

aws.amazon.com/documentdb/resources

www.geomesa.org/documentation/stable/user/index.html

developer.microsoft.com/en-us/access

learn.microsoft.com/azure/cosmos-db

sitewhere1.sitewhere.io/index.html

Developer

CCRi and others

Microsoft

SiteWhere

Initial release

2019

2014

1992

2014

2010

Current release

5.0.0, May 2024

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

commercial

Bundled with Microsoft Office

commercial

Open Source

Common Public Attribution License Version 1.0

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

Scala

C++

Java

Server operating systems

hosted

Windows

Not a real database server, but making use of DLLs

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

predefined scheme

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

yes

but not compliant to any SQL standard

SQL-like query language

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

ADO.NET
DAO
ODBC
OLE DB

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP REST

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

JavaScript

Triggers

yes

since Access 2010 using the ACE-engine

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

none

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

depending on storage layer

none

yes

Implicit feature of the cloud service

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

ACID

but no files for transaction logging

Multi-item ACID transactions with snapshot isolation within a partition

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.

depending on storage layer

User concepts

Access control

Access rights for users and roles

yes

depending on the DBMS used for storage

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

Access rights can be defined down to the item level

Users with fine-grained authorization concept

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