DBMS > Blueflood vs. dBASE vs. Google Cloud Firestore vs. Microsoft Azure Cosmos DB vs. Sphinx

System Properties Comparison Blueflood vs. dBASE vs. Google Cloud Firestore vs. Microsoft Azure Cosmos DB vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

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.

Globally distributed, horizontally scalable, multi-model database service

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Time Series DBMS

Relational DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Search engine

Secondary database models

Spatial DBMS

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	10.34
Rank	#44	Overall
	#28	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

blueflood.io

www.dbase.com

firebase.google.com/products/firestore

azure.microsoft.com/services/cosmos-db

sphinxsearch.com

Technical documentation

github.com/rax-maas/blueflood/wiki

www.dbase.com/support/knowledgebase

firebase.google.com/docs/firestore

learn.microsoft.com/azure/cosmos-db

sphinxsearch.com/docs

Developer

Rackspace

Asthon Tate

Google

Microsoft

Sphinx Technologies Inc.

Initial release

2013

1979

2017

2014

2001

Current release

dBASE 2019, 2019

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPL version 2, commercial licence 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

C++

Server operating systems

Linux
OS X

DOS

dBase Classic
Windows

dBase Pro

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

predefined scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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 properties auto-indexed by default

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

SQL-like query language (SphinxQL)

APIs and other access methods

HTTP REST

none

The IDE can access other DBMS or ODBC-sources.

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

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Proprietary protocol

Supported programming languages

dBase proprietary IDE

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

yes, Firebase Rules & Cloud Functions

JavaScript

Triggers

yes, with Cloud Functions

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

Implicit feature of the cloud service

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

Multi-source replication

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session 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

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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

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

Access rights can be defined down to the item level

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