DBMS > OpenMLDB vs. SAP HANA vs. Valentina Server

System Properties Comparison OpenMLDB vs. SAP HANA vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

An open-source machine learning database that provides a feature platform for training and inference

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

Object-relational database and reports server

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.02
Rank	#367	Overall
	#37	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

openmldb.ai

www.sap.com/products/hana.html

www.valentina-db.net

Technical documentation

openmldb.ai/docs/zh/main

help.sap.com/hana

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

4 Paradigm Inc.

SAP

Paradigma Software

Initial release

2020

2010

1999

Current release

2024-2 February 2024

2.0 SPS07 (April 4, 2023), April 2023

5.7.5

License

Commercial or Open Source

Open Source

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java, Scala

Server operating systems

Linux

Appliance or cloud-service

Linux
OS X
Windows

Data scheme

Fixed 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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
SQLAlchemy

JDBC
ODBC

ODBC

Supported programming languages

C++
Go
Java
Python
Scala

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

SQLScript, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

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

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

yes

fine grained access rights according to SQL-standard

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