DBMS > Hyprcubd vs. Ingres vs. NCache vs. Oracle vs. SQLite

System Properties Comparison Hyprcubd vs. Ingres vs. NCache vs. Oracle vs. SQLite

Editorial information provided by DB-Engines

Name

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

Description

Serverless Time Series DBMS

Well established RDBMS

Open-Source and Enterprise in-memory Key-Value Store

Widely used RDBMS

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Document store
Search engine

Using distributed Lucene

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

hyprcubd.com (offline)

www.actian.com/databases/ingres

www.alachisoft.com/ncache

www.oracle.com/database

www.sqlite.org

Technical documentation

docs.actian.com/ingres

www.alachisoft.com/resources/docs

docs.oracle.com/en/database

www.sqlite.org/docs.html

Developer

Hyprcubd, Inc.

Actian Corporation

Alachisoft

Oracle

Dwayne Richard Hipp

Initial release

1974

originally developed at University Berkely in early 1970s

2005

1980

2000

Current release

11.2, May 2022

5.3.3, April 2024

23c, September 2023

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Enterprise Edition available

commercial

restricted free version is available

Open Source

Public Domain

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#, .NET, .NET Core, Java

C and C++

Server operating systems

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

server-less

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

yes

dynamic column types

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

yes

not rigid because of 'dynamic typing' concept.

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.

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

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

with proprietary extensions

yes

SQL-92 is not fully supported

APIs and other access methods

gRPC (https)

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

IDistributedCache
JCache
LINQ
Proprietary native API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

support for stored procedures with SQL-Server CLR

PL/SQL

also stored procedures in Java possible

Triggers

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Ingres Star to access multiple databases simultaneously

yes

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Ingres Replicator

yes, with selectable consistency level

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

via file-system locks

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

token access

fine grained access rights according to SQL-standard

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
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Market metrics

Market Leader in .NET Distributed Caching since 2005.
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Licensing and pricing models

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