DBMS > 4D vs. H2 vs. Spark SQL vs. YDB

System Properties Comparison 4D vs. H2 vs. Spark SQL vs. YDB

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

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

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Document store
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	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

www.4d.com

www.h2database.com

spark.apache.org/sql

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

developer.4d.com

www.h2database.com/html/main.html

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

ydb.tech/en/docs

Developer

4D, Inc

Thomas Mueller

Apache Software Foundation

Yandex

Initial release

1984

2005

2014

2019

Current release

v20, April 2023

2.2.220, July 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

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

Open Source

Apache 2.0

Open Source

Apache 2.0; commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Scala

Server operating systems

OS X
Windows

All OS with a Java VM

Linux
OS X
Windows

Linux

Data scheme

yes

Flexible Schema (defined schema, partial schema, 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

yes

SQL-like DML and DDL statements

SQL-like query language (YQL)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

4D proprietary IDE
PHP

Java

Java
Python
R
Scala

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

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

none

Active-passive shard replication

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

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)

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

fine grained access rights according to SQL-standard

Access rights defined for Yandex Cloud users

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More resources

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