DBMS > H2 vs. OpenEdge vs. Spark SQL vs. Yanza

System Properties Comparison H2 vs. OpenEdge vs. Spark SQL vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Application development environment with integrated database management system

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

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

www.h2database.com

www.progress.com/openedge

spark.apache.org/sql

yanza.com

Technical documentation

www.h2database.com/html/main.html

documentation.progress.com/output/ua/OpenEdge_latest

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

Developer

Thomas Mueller

Progress Software Corporation

Apache Software Foundation

Yanza

Initial release

2005

1984

2014

2015

Current release

2.2.220, July 2023

OpenEdge 12.2, March 2020

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

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

commercial

Open Source

Apache 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

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

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

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-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

HTTP API

Supported programming languages

Java

Progress proprietary ABL (Advanced Business Language)

Java
Python
R
Scala

any language that supports HTTP calls

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

since Version 11.4

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

none

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, 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

fine grained access rights according to SQL-standard

Users and groups

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More resources

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