DBMS > dBASE vs. Google Cloud Bigtable vs. Ingres vs. Microsoft SQL Server vs. mSQL

System Properties Comparison dBASE vs. Google Cloud Bigtable vs. Ingres vs. Microsoft SQL Server vs. mSQL

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.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Well established RDBMS

Microsofts flagship relational DBMS

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Relational DBMS

Key-value store
Wide column store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Website

www.dbase.com

cloud.google.com/bigtable

www.actian.com/databases/ingres

www.microsoft.com/en-us/sql-server

hughestech.com.au/products/msql

Technical documentation

www.dbase.com/support/knowledgebase

cloud.google.com/bigtable/docs

docs.actian.com/ingres

learn.microsoft.com/en-US/sql/sql-server

Developer

Asthon Tate

Google

Actian Corporation

Microsoft

Hughes Technologies

Initial release

1979

2015

1974

originally developed at University Berkely in early 1970s

1989

1994

Current release

dBASE 2019, 2019

11.2, May 2022

SQL Server 2022, November 2022

4.4, October 2021

License

Commercial or Open Source

commercial

restricted free version is available

commercial

free licenses can be provided

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

DOS

dBase Classic
Windows

dBase Pro

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
Windows

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

Data scheme

yes

schema-free

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

none

The IDE can access other DBMS or ODBC-sources.

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC

Supported programming languages

dBase proprietary IDE

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Internal replication in Colossus, and regional replication between two clusters in different zones

Ingres Replicator

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

none

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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