DBMS > dBASE vs. Google Cloud Firestore vs. Hazelcast vs. Snowflake

System Properties Comparison dBASE vs. Google Cloud Firestore vs. Hazelcast vs. Snowflake

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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.

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.

A widely adopted in-memory data grid

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	11.18
Rank	#44	Overall
	#28	Relational DBMS

Score	8.96
Rank	#48	Overall
	#8	Document stores

Score	6.87
Rank	#55	Overall
	#6	Key-value stores

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

www.dbase.com

firebase.google.com/products/firestore

hazelcast.com

www.snowflake.com

Technical documentation

www.dbase.com/support/knowledgebase

firebase.google.com/docs/firestore

hazelcast.org/imdg/docs

docs.snowflake.net/manuals/index.html

Developer

Asthon Tate

Google

Hazelcast

Snowflake Computing Inc.

Initial release

1979

2017

2008

2014

Current release

dBASE 2019, 2019

5.3.6, November 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

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

Java

Server operating systems

DOS

dBase Classic
Windows

dBase Pro

hosted

All OS with a Java VM

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

none

The IDE can access other DBMS or ODBC-sources.

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

JCache
JPA
Memcached protocol
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

dBase proprietary IDE

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

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

yes, Firebase Rules & Cloud Functions

yes

Event Listeners, Executor Services

user defined functions

Triggers

yes, with Cloud Functions

yes

Events

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

yes

Replicated Map

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

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

yes

one or two-phase-commit; repeatable reads; read commited

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

Role-based access control

Users with fine-grained authorization concept, user roles and pluggable authentication

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