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

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

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Editorial information provided by DB-Engines

Name

Description

dBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.

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 embeddable, in-process RDBMS

Cloud or on-premises 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

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	15.33
Rank	#42	Overall
	#26	Relational DBMS

Score	146.50
Rank	#9	Overall
	#6	Relational DBMS

Score	138.87
Rank	#10	Overall
	#7	Relational DBMS

Score	20.13
Rank	#37	Overall
	#23	Relational DBMS

Website

www.dbase.com

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

www.sqlite.org

www.vertica.com

Technical documentation

www.dbase.com/support/knowledgebase

developer.microsoft.com/en-us/access

www.sqlite.org/docs.html

vertica.com/documentation

Developer

Asthon Tate

Microsoft

Dwayne Richard Hipp

Micro Focus

prior to that Hewlett Packard

Initial release

1979

1992

2000

2005

Current release

dBASE 2019, 2019

1902 (16.0.11328.20222), March 2019

3.39.1 (13 July 2022), July 2022

11.1, February 2022

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

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.

Vertica Accelerator’s high-performance analytics and machine learning with SQL or Python is available as a managed service.

Implementation language

C++

Server operating systems

DOS

dBase Classic
Windows

dBase Pro

Windows

Not a real database server, but making use of DLLs

server-less

Linux

Data scheme

yes

dynamic column types

yes, but unstructured data can be stored in specific Flex-Tables

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

yes: BINARY, BOOLEAN, CHAR, VARCHAR, LONG VARCHAR, DATE, TIME, TIMESTAMP, INTERVAL, INTERVAL DAY TO SECOND, INTERVAL YEAR TO MONTH, DOUBLE PRECISION, FLOAT, INTEGER, BIGINT, SMALLINT,NUMERIC, DECIMAL, NUMBER, MONEY,GEOMETRY

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

No Indexes Required

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

none

The IDE can access other DBMS or ODBC-sources.

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

dBase proprietary IDE

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

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++
Java
Perl
PHP
Python
R

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

yes

since Access 2010 using the ACE-engine

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

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

not for dBase internal data, but IDE does support transactions when accessing external DBMS

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

Access rights for users and roles

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

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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