DBMS > dBASE vs. Google BigQuery vs. GridDB vs. YDB

System Properties Comparison dBASE vs. Google BigQuery vs. GridDB vs. YDB

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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.

Large scale data warehouse service with append-only tables

Scalable in-memory time series database optimized for IoT and Big Data

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Time Series DBMS

Document store
Relational DBMS

Secondary database models

Key-value store
Relational DBMS

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

Score	9.16
Rank	#43	Overall
	#27	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	0.39
Rank	#269	Overall
	#43	Document stores
	#126	Relational DBMS

Website

www.dbase.com

cloud.google.com/bigquery

griddb.net

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

www.dbase.com/support/knowledgebase

cloud.google.com/bigquery/docs

docs.griddb.net

ydb.tech/en/docs

Developer

Asthon Tate

Google

Toshiba Corporation

Yandex

Initial release

1979

2010

2013

2019

Current release

dBASE 2019, 2019

5.1, August 2022

License

Commercial or Open Source

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

Apache 2.0; commercial license available

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++

Server operating systems

DOS

dBase Classic
Windows

dBase Pro

hosted

Linux

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like query language (YQL)

APIs and other access methods

none

The IDE can access other DBMS or ODBC-sources.

RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

dBase proprietary IDE

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

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

none

Source-replica replication

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

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 at container level

ACID

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

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 can be defined per database

Access rights defined for Yandex Cloud users

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