DBMS > Amazon Redshift vs. dBASE vs. Google Cloud Firestore vs. Heroic vs. Infobright

System Properties Comparison Amazon Redshift vs. dBASE vs. Google Cloud Firestore vs. Heroic vs. Infobright

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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.

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Primary database model

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Website

aws.amazon.com/redshift

www.dbase.com

firebase.google.com/products/firestore

github.com/spotify/heroic

ignitetech.com/softwarelibrary/infobrightdb

Technical documentation

docs.aws.amazon.com/redshift

www.dbase.com/support/knowledgebase

firebase.google.com/docs/firestore

spotify.github.io/heroic

Developer

Amazon (based on PostgreSQL)

Asthon Tate

Google

Spotify

Ignite Technologies Inc.; formerly InfoBright Inc.

Initial release

2012

1979

2017

2014

2005

Current release

dBASE 2019, 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

Linux
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.

Secondary indexes

restricted

yes

via Elasticsearch

Knowledge Grid Technology used instead

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

none

The IDE can access other DBMS or ODBC-sources.

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

dBase proprietary IDE

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

The IDE can access stored procedures in other database systems.

yes, Firebase Rules & Cloud Functions

Triggers

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

yes

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

fine grained access rights according to SQL-standard

Access rights for users and roles

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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