DBMS > GeoMesa vs. Microsoft Access vs. Microsoft Azure Cosmos DB vs. SiteWhere vs. Sphinx

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

Editorial information provided by DB-Engines

Name

Description

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

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Spatial DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Search engine

Secondary database models

Spatial DBMS

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

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

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

www.geomesa.org

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

azure.microsoft.com/services/cosmos-db

github.com/sitewhere/sitewhere

sphinxsearch.com

Technical documentation

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

sphinxsearch.com/docs

Developer

CCRi and others

Microsoft

SiteWhere

Sphinx Technologies Inc.

Initial release

2014

1992

2014

2010

2001

Current release

5.0.0, May 2024

1902 (16.0.11328.20222), March 2019

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Bundled with Microsoft Office

commercial

Open Source

Common Public Attribution License Version 1.0

Open Source

GPL version 2, commercial licence available

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

C++

Server operating systems

Windows

Not a real database server, but making use of DLLs

hosted

Linux
OS X
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

predefined scheme

yes

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

yes

full-text index on all search fields

SQL

Support of SQL

yes

but not compliant to any SQL standard

SQL-like query language

SQL-like query language (SphinxQL)

APIs and other access methods

ADO.NET
DAO
ODBC
OLE DB

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

HTTP REST

Proprietary protocol

Supported programming languages

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

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

depending on storage layer

none

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

none

yes

Implicit feature of the cloud service

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

Transaction concepts

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

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

The original contents of fields are not stored in the Sphinx index.

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

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.