DBMS > GeoMesa vs. Google BigQuery vs. MaxDB vs. Microsoft Access vs. TimesTen

System Properties Comparison GeoMesa vs. Google BigQuery vs. MaxDB vs. Microsoft Access vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

A robust and reliable RDBMS optimized to run all major SAP solutions

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.)

In-Memory RDBMS compatible to Oracle

Primary database model

Spatial DBMS

Relational DBMS

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

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.geomesa.org

cloud.google.com/bigquery

maxdb.sap.com

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

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

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

cloud.google.com/bigquery/docs

maxdb.sap.com/documentation

developer.microsoft.com/en-us/access

docs.oracle.com/database/timesten-18.1

Developer

CCRi and others

Google

SAP, acquired from Software AG (Adabas-D) in 1997

Microsoft

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2014

2010

1984

1992

1998

Current release

4.0.5, February 2024

7.9.10.12, February 2024

1902 (16.0.11328.20222), March 2019

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Limited community edition free

commercial

Bundled with Microsoft Office

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

Scala

C++

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows

Windows

Not a real database server, but making use of DLLs

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

yes

but not compliant to any SQL standard

yes

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
WebDAV

ADO.NET
DAO
ODBC
OLE DB

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C#
Java
Perl
PHP
Python

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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

since Access 2010 using the ACE-engine

PL/SQL

Triggers

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

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