DBMS > 4D vs. Databricks vs. Galaxybase vs. H2

System Properties Comparison 4D vs. Databricks vs. Galaxybase vs. H2

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

Scalable, ACID-compliant native distributed parallel graph platform

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Primary database model

Relational DBMS

Document store
Relational DBMS

Graph DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Website

Technical documentation

developer.4d.com

docs.databricks.com

www.h2database.com/html/main.html

Developer

4D, Inc

Databricks

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Thomas Mueller

Initial release

1984

2013

2017

2005

Current release

v20, April 2023

Nov 20, November 2021

2.2.220, July 2023

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

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

C and Java

Java

Server operating systems

OS X
Windows

hosted

Linux

All OS with a Java VM

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

Strong typed schema

yes

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

with Databricks SQL

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC
RESTful HTTP API

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

JDBC
ODBC

Supported programming languages

4D proprietary IDE
PHP

Python
R
Scala

Go
Java
Python

Java

Server-side scripts

Stored procedures

yes

user defined functions and aggregates

user defined procedures and functions

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

With clustering: 2 database servers on different computers operate on identical copies of a database

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Role-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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14 June 2024, SiliconANGLE News

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