DBMS > 4D vs. dBASE vs. Google BigQuery vs. Google Cloud Bigtable vs. VictoriaMetrics

System Properties Comparison 4D vs. dBASE vs. Google BigQuery vs. Google Cloud Bigtable vs. VictoriaMetrics

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

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

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Relational DBMS

Key-value store
Wide column store

Time Series DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

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

Score	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Website

www.4d.com

www.dbase.com

cloud.google.com/bigquery

cloud.google.com/bigtable

victoriametrics.com

Technical documentation

developer.4d.com

www.dbase.com/support/knowledgebase

cloud.google.com/bigquery/docs

cloud.google.com/bigtable/docs

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

4D, Inc

Asthon Tate

Google

VictoriaMetrics

Initial release

1984

1979

2010

2015

2018

Current release

v20, April 2023

dBASE 2019, 2019

v1.91, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

Server operating systems

OS X
Windows

DOS

dBase Classic
Windows

dBase Pro

hosted

FreeBSD
Linux
macOS
OpenBSD

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

close to SQL 92

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

none

The IDE can access other DBMS or ODBC-sources.

RESTful HTTP/JSON API

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

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

4D proprietary IDE
PHP

dBase proprietary IDE

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

The IDE can access stored procedures in other database systems.

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

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

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

Since BigQuery is designed for querying data

Atomic single-row operations

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.

User concepts

Access control

Users and groups

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

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