DBMS > EsgynDB vs. Greenplum vs. Hyprcubd vs. Oracle NoSQL vs. PostgreSQL

System Properties Comparison EsgynDB vs. Greenplum vs. Hyprcubd vs. Oracle NoSQL vs. PostgreSQL

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

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.

Serverless Time Series DBMS

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Primary database model

Relational DBMS

Time Series DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Website

www.esgyn.cn

greenplum.org

hyprcubd.com (offline)

www.oracle.com/database/nosql/technologies/nosql

www.postgresql.org

Technical documentation

docs.greenplum.org

docs.oracle.com/en/database/other-databases/nosql-database/index.html

www.postgresql.org/docs

Developer

Esgyn

Pivotal Software Inc.

Hyprcubd, Inc.

Oracle

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2015

2005

2011

1989

1989: Postgres, 1996: PostgreSQL

Current release

7.0.0, September 2023

24.1, May 2024

16.3, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++, Java

Java

Server operating systems

Linux

hosted

Linux
Solaris SPARC/x86

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

since Version 4.2

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

SQL-like DML and DDL statements

yes

standard with numerous extensions

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC

gRPC (https)

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
Java
Perl
Python
R

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

Java Stored Procedures

yes

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

partitioning by range, list and (since PostgreSQL 11) by hash

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

configurable

ACID within a storage node (=shard)

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

off heap cache

User concepts

Access control

fine grained access rights according to SQL-standard

token access

Access rights for users and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

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