DBMS > 4D vs. GBase vs. HBase vs. Microsoft SQL Server vs. Spark SQL

System Properties Comparison 4D vs. GBase vs. HBase vs. Microsoft SQL Server vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

Microsofts flagship relational DBMS

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Relational DBMS

Wide column store

Relational DBMS

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	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

www.4d.com

www.gbase.cn

hbase.apache.org

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

spark.apache.org/sql

Technical documentation

developer.4d.com

hbase.apache.org/book.html

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

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

4D, Inc

General Data Technology Co., Ltd.

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

Apache Software Foundation

Initial release

1984

2004

2008

1989

2014

Current release

v20, April 2023

GBase 8a, GBase 8s, GBase 8c

2.3.4, January 2021

SQL Server 2022, November 2022

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

restricted free version is available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C, Java, Python

Java

C++

Scala

Server operating systems

OS X
Windows

Linux

Linux
Unix
Windows

using Cygwin

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

Standard with numerous extensions

yes

SQL-like DML and DDL statements

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

ADO.NET
C API
JDBC
ODBC

Java API
RESTful HTTP API
Thrift

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

JDBC
ODBC

Supported programming languages

4D proprietary IDE
PHP

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions

yes

Coprocessors in Java

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

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

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

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

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

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

yes

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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