DBMS > Greenplum vs. OpenMLDB vs. SAP HANA vs. TimesTen

System Properties Comparison Greenplum vs. OpenMLDB vs. SAP HANA vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

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

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.10
Rank	#359	Overall
	#36	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

greenplum.org

openmldb.ai

www.sap.com/products/hana.html

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.greenplum.org

openmldb.ai/docs/zh/main

help.sap.com/hana

docs.oracle.com/database/timesten-18.1

Developer

Pivotal Software Inc.

4 Paradigm Inc.

SAP

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2005

2020

2010

1998

Current release

7.0.0, September 2023

2024-2 February 2024

2.0 SPS07 (April 4, 2023), April 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache 2.0

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

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

Implementation language

C++, Java, Scala

Server operating systems

Linux

Appliance or cloud-service

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

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.

yes

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

JDBC
SQLAlchemy

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
Java
Perl
Python
R

C++
Go
Java
Python
Scala

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

SQLScript, R

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

by means of logfiles and checkpoints

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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