DBMS > dBASE vs. Google BigQuery vs. Kinetica vs. Microsoft Azure SQL Database vs. searchxml

System Properties Comparison dBASE vs. Google BigQuery vs. Kinetica vs. Microsoft Azure SQL Database vs. searchxml

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.

Large scale data warehouse service with append-only tables

Fully vectorized database across both GPUs and CPUs

Database as a Service offering with high compatibility to Microsoft SQL Server

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS

Native XML DBMS
Search engine

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	10.34
Rank	#44	Overall
	#28	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

www.dbase.com

cloud.google.com/bigquery

www.kinetica.com

azure.microsoft.com/en-us/products/azure-sql/database

www.searchxml.net/category/products

Technical documentation

www.dbase.com/support/knowledgebase

cloud.google.com/bigquery/docs

docs.kinetica.com

docs.microsoft.com/en-us/azure/azure-sql

www.searchxml.net/support/handouts

Developer

Asthon Tate

Google

Kinetica

Microsoft

informationpartners gmbh

Initial release

1979

2010

2012

2010

2015

Current release

dBASE 2019, 2019

7.1, August 2021

V12

1.0

License

Commercial or Open Source

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

C, C++

C++

Server operating systems

DOS

dBase Classic
Windows

dBase Pro

hosted

Linux

hosted

Windows

Data scheme

yes

schema-free

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

none

The IDE can access other DBMS or ODBC-sources.

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

dBase proprietary IDE

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

user defined functions

in JavaScript

user defined functions

Transact SQL

yes

on the application server

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes, with always 3 replicas available

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

Since BigQuery is designed for querying data

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

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

GPU vRAM or System RAM

User concepts

Access control

Access rights for users and roles

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

Google Cloud Identity & Access Management (IAM)

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

Domain, group and role-based access control at the document level and for application services

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