DBMS > EsgynDB vs. Hyprcubd vs. IBM Db2 warehouse vs. Ingres vs. Netezza

System Properties Comparison EsgynDB vs. Hyprcubd vs. IBM Db2 warehouse vs. Ingres vs. Netezza

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

Serverless Time Series DBMS

Cloud-based data warehousing service

Well established RDBMS

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

www.esgyn.cn

hyprcubd.com (offline)

www.ibm.com/products/db2/warehouse

www.actian.com/databases/ingres

www.ibm.com/products/netezza

Technical documentation

docs.actian.com/ingres

Developer

Esgyn

Hyprcubd, Inc.

IBM

Actian Corporation

IBM

Initial release

2015

2014

1974

originally developed at University Berkely in early 1970s

2000

Current release

11.2, May 2022

License

Commercial or Open Source

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

Server operating systems

Linux

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux

included in appliance

Data scheme

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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.

Import/export of XML data possible

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

gRPC (https)

.NET Client API
JDBC
ODBC
OLE DB

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

Java Stored Procedures

PL/SQL, SQL PL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

Ingres Replicator

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

Eventual Consistency

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

MVCC

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

token access

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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