DBMS > Microsoft Access vs. OpenQM vs. SQLite vs. Vertica

System Properties Comparison Microsoft Access vs. OpenQM vs. SQLite vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

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.)

QpenQM is a high-performance, self-tuning, multi-value DBMS

Widely used embeddable, in-process RDBMS

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Relational DBMS

Multivalue DBMS

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

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

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.sqlite.org

www.vertica.com

Technical documentation

developer.microsoft.com/en-us/access

www.sqlite.org/docs.html

vertica.com/documentation

Developer

Microsoft

Rocket Software, originally Martin Phillips

Dwayne Richard Hipp

OpenText

previously Micro Focus and Hewlett Packard

Initial release

1992

1993

2000

2005

Current release

1902 (16.0.11328.20222), March 2019

3.4-12

3.46.0 (23 May 2024), May 2024

12.0.3, January 2023

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

Open Source

GPLv2, extended commercial license available

Open Source

Public Domain

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

Windows

Not a real database server, but making use of DLLs

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

server-less

Linux

Data scheme

yes

with some exceptions

yes

dynamic column types

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

but not compliant to any SQL standard

yes

SQL-92 is not fully supported

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

ADO.NET
DAO
ODBC
OLE DB

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

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

.Net
Basic
C
Java
Objective C
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

since Access 2010 using the ACE-engine

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

none

yes

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

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

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

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Licensing and pricing models

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