DBMS > 4D vs. Google Cloud Firestore vs. HBase vs. Microsoft SQL Server vs. STSdb

System Properties Comparison 4D vs. Google Cloud Firestore vs. HBase vs. Microsoft SQL Server vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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.

Wide-column store based on Apache Hadoop and on concepts of BigTable

Microsofts flagship relational DBMS

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

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

Website

www.4d.com

firebase.google.com/products/firestore

hbase.apache.org

www.microsoft.com/en-us/sql-server

github.com/STSSoft/STSdb4

Technical documentation

developer.4d.com

firebase.google.com/docs/firestore

hbase.apache.org/book.html

learn.microsoft.com/en-US/sql/sql-server

Developer

4D, Inc

Google

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

STS Soft SC

Initial release

1984

2017

2008

1989

2011

Current release

v20, April 2023

2.3.4, January 2021

SQL Server 2022, November 2022

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

restricted free version is available

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Server operating systems

OS X
Windows

hosted

Linux
Unix
Windows

using Cygwin

Linux
Windows

Windows

Data scheme

yes

schema-free

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

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

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

.NET Client API

Supported programming languages

4D proprietary IDE
PHP

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

C
C#
C++
Groovy
Java
PHP
Python
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C#
Java

Server-side scripts

Stored procedures

yes

yes, Firebase Rules & Cloud Functions

yes

Coprocessors in Java

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

none

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Single row ACID (across millions of columns)

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

Users and groups

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 Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

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