DBMS > Hyprcubd vs. Oracle NoSQL vs. Realm vs. Valentina Server

System Properties Comparison Hyprcubd vs. Oracle NoSQL vs. Realm vs. Valentina Server

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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

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Object-relational database and reports server

Primary database model

Time Series DBMS

Document store
Key-value store
Relational DBMS

Document store

Relational DBMS

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

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

hyprcubd.com (offline)

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

realm.io

www.valentina-db.net

Technical documentation

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

realm.io/docs

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Hyprcubd, Inc.

Oracle

Realm, acquired by MongoDB in May 2019

Paradigma Software

Initial release

2011

2014

1999

Current release

23.3, December 2023

5.7.5

License

Commercial or Open Source

commercial

Open Source

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

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

Java

Server operating systems

hosted

Linux
Solaris SPARC/x86

Android
Backend: server-less
iOS
Windows

Linux
OS X
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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

yes

APIs and other access methods

gRPC (https)

RESTful HTTP API

ODBC

Supported programming languages

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

.Net
Java

with Android only
Objective-C
React Native
Swift

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

yes

Triggers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

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

yes

In-Memory realm

yes

User concepts

Access control

token access

Access rights for users and roles

yes

fine grained access rights according to SQL-standard

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