DBMS > Amazon SimpleDB vs. dBASE vs. Google BigQuery vs. Hive vs. STSdb

System Properties Comparison Amazon SimpleDB vs. dBASE vs. Google BigQuery vs. Hive vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Key-value store

Relational DBMS

Key-value store

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

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

aws.amazon.com/simpledb

www.dbase.com

cloud.google.com/bigquery

hive.apache.org

github.com/STSSoft/STSdb4

Technical documentation

docs.aws.amazon.com/simpledb

www.dbase.com/support/knowledgebase

cloud.google.com/bigquery/docs

cwiki.apache.org/confluence/display/Hive/Home

Developer

Amazon

Asthon Tate

Google

Apache Software Foundation

initially developed by Facebook

STS Soft SC

Initial release

2007

1979

2010

2012

2011

Current release

dBASE 2019, 2019

3.1.3, April 2022

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

GPLv2, 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

Java

Server operating systems

hosted

DOS

dBase Classic
Windows

dBase Pro

hosted

All OS with a Java VM

Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

All columns are indexed automatically

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API

none

The IDE can access other DBMS or ODBC-sources.

RESTful HTTP/JSON API

JDBC
ODBC
Thrift

.NET Client API

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

dBase proprietary IDE

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
PHP
Python

C#
Java

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

user defined functions

in JavaScript

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

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

Since BigQuery is designed for querying data

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

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

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