DBMS > Altibase vs. EsgynDB vs. Hyprcubd

System Properties Comparison Altibase vs. EsgynDB vs. Hyprcubd

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Editorial information provided by DB-Engines

Name

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

Description

An enterprise grade, high-performance RDBMS

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

Serverless Time Series DBMS

Primary database model

Relational DBMS

Time Series DBMS

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

Score	1.00
Rank	#194	Overall
	#91	Relational DBMS

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Website

altibase.com

www.esgyn.cn

hyprcubd.com (offline)

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

Developer

Altibase

Esgyn

Hyprcubd, Inc.

Initial release

1999

2015

Current release

v7.3, 2023, August 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

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++

C++, Java

Server operating systems

AIX
HP-UX
Linux

Linux

hosted

Data scheme

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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

ANSI SQL-92

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
ODBC

gRPC (https)

Supported programming languages

C
C++
Java

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

stored procedures and stored functions

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

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

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

token access

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More resources

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provided by Google News

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