DBMS > 4D vs. Apache Drill vs. Google Cloud Firestore vs. Newts

System Properties Comparison 4D vs. Apache Drill vs. Google Cloud Firestore vs. Newts

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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 based on Cassandra

Primary database model

Relational DBMS

Document store
Relational DBMS

Document store

Time Series DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Website

www.4d.com

drill.apache.org

firebase.google.com/products/firestore

opennms.github.io/newts

Technical documentation

developer.4d.com

drill.apache.org/docs

firebase.google.com/docs/firestore

github.com/OpenNMS/newts/wiki

Developer

4D, Inc

Apache Software Foundation

Google

OpenNMS Group

Initial release

1984

2012

2017

2014

Current release

v20, April 2023

1.20.3, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

OS X
Windows

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL SELECT statement is SQL:2003 compliant

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC
RESTful HTTP API

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

HTTP REST
Java API

Supported programming languages

4D proprietary IDE
PHP

C++

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

Java

Server-side scripts

Stored procedures

yes

user defined functions

yes, Firebase Rules & Cloud Functions

Triggers

yes

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

User concepts

Access control

Users and groups

Depending on the underlying data source

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

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More resources

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Recent citations in the news

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19 May 2015, Datanami

Apache Drill Eliminates ETL, Data Transformation for MapR Database
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