DBMS > Apache Pinot vs. Cubrid vs. openGauss vs. SAP HANA

System Properties Comparison Apache Pinot vs. Cubrid vs. openGauss vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

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

Primary database model

Relational DBMS

Secondary database models

Document store
Spatial 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	0.35
Rank	#274	Overall
	#128	Relational DBMS

Score	0.97
Rank	#189	Overall
	#86	Relational DBMS

Score	1.11
Rank	#175	Overall
	#79	Relational DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Website

pinot.apache.org

cubrid.com (korean)
cubrid.org (english)

gitee.com/opengauss
opengauss.org

www.sap.com/products/hana.html

Technical documentation

docs.pinot.apache.org

cubrid.org/manuals

docs.opengauss.org/en
gitee.com/opengauss/docs

help.sap.com/hana

Developer

Apache Software Foundation and contributors

CUBRID Corporation, CUBRID Foundation

Huawei and openGauss community

SAP

Initial release

2015

2008

2019

2010

Current release

1.0.0, September 2023

11.0, January 2021

3.0, March 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 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

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Implementation language

Java

C, C++, Java

Server operating systems

All OS with a Java JDK11 or higher

Linux
Windows

Linux

Appliance or cloud-service

Data scheme

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

SQL-like query language

yes

ANSI SQL 2011

yes

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC

Supported programming languages

Go
Java
Python

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

C
C++
Java

Server-side scripts

Stored procedures

Java Stored Procedures

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

horizontal partitioning (by range, list and hash)

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

Access rights for users, groups and roles according to SQL-standard

yes

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