DBMS > OpenEdge vs. SAP HANA vs. UniData,UniVerse vs. Vertica

System Properties Comparison OpenEdge vs. SAP HANA vs. UniData,UniVerse vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

In-memory, column based data store. Available as appliance or cloud service

MultiValue database and application server with SQL mapping layer and meta database capabilities

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Relational DBMS

Multivalue DBMS

Relational DBMS

Column oriented

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	3.69
Rank	#78	Overall
	#42	Relational DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	2.25
Rank	#112	Overall
	#2	Multivalue DBMS

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Website

www.progress.com/openedge

www.sap.com/products/hana.html

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

www.vertica.com

Technical documentation

documentation.progress.com/output/ua/OpenEdge_latest

help.sap.com/hana

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

vertica.com/documentation

Developer

Progress Software Corporation

SAP

Rocket Software

OpenText

previously Micro Focus and Hewlett Packard

Initial release

1984

2010

1985

2005

Current release

OpenEdge 12.2, March 2020

2.0 SPS07 (April 4, 2023), April 2023

12.0.3, January 2023

License

Commercial or Open Source

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

also available as a cloud based service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

AIX
HP-UX
Linux
Solaris
Windows

Appliance or cloud-service

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

yes

schema-free

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

optional

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

close to SQL 92

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

JDBC
ODBC

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Progress proprietary ABL (Advanced Business Language)

.Net
Basic

U2 Basic
C
Java

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes

SQLScript, R

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

U2 Basic

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

since Version 11.4

yes

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Source-replica replication

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

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

configurable

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 rights according to SQL-standard and operating system based

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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