DBMS > EsgynDB vs. Greenplum vs. HyperSQL vs. Oracle Rdb vs. Pinecone

System Properties Comparison EsgynDB vs. Greenplum vs. HyperSQL vs. Oracle Rdb vs. Pinecone

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A managed, cloud-native vector database

Primary database model

Relational DBMS

Vector DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	3.23
Rank	#92	Overall
	#3	Vector DBMS

Website

www.esgyn.cn

greenplum.org

hsqldb.org

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

www.pinecone.io

Technical documentation

docs.greenplum.org

hsqldb.org/web/hsqlDocsFrame.html

www.oracle.com/database/technologies/related/rdb-doc.html

docs.pinecone.io/docs/overview

Developer

Esgyn

Pivotal Software Inc.

Oracle, originally developed by Digital Equipment Corporation (DEC)

Pinecone Systems, Inc

Initial release

2015

2005

2001

1984

2019

Current release

7.0.0, September 2023

2.7.2, June 2023

7.4.1.1, 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

based on BSD license

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++, Java

Java

Server operating systems

Linux

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

HP Open VMS

hosted

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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

ADO.NET
JDBC
ODBC

JDBC
ODBC

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
Java
Perl
Python
R

All languages supporting JDBC/ODBC
Java

Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes, on a single node

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

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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