DBMS > Cubrid vs. NCache vs. Sphinx vs. SQLite vs. SWC-DB

System Properties Comparison Cubrid vs. NCache vs. Sphinx vs. SQLite vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

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

Open source search engine for searching in data from different sources, e.g. relational databases

Widely used embeddable, in-process RDBMS

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Document store
Search engine

Using distributed Lucene

Time Series DBMS

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

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	0.98
Rank	#196	Overall
	#29	Key-value stores

Score	6.03
Rank	#60	Overall
	#6	Search engines

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Score	0.01
Rank	#387	Overall
	#13	Wide column stores

Website

cubrid.com (korean)
cubrid.org (english)

www.alachisoft.com/ncache

sphinxsearch.com

www.sqlite.org

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

cubrid.org/manuals

www.alachisoft.com/resources/docs

sphinxsearch.com/docs

www.sqlite.org/docs.html

Developer

CUBRID Corporation, CUBRID Foundation

Alachisoft

Sphinx Technologies Inc.

Dwayne Richard Hipp

Alex Kashirin

Initial release

2008

2005

2001

2000

2020

Current release

11.0, January 2021

5.3.3, April 2024

3.5.1, February 2023

3.45.3 (15 April 2024), April 2024

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Enterprise Edition available

Open Source

GPL version 2, commercial licence available

Open Source

Public Domain

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Java

C#, .NET, .NET Core, Java

C++

Server operating systems

Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

server-less

Linux

Data scheme

yes

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

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

SQL-like query language (SphinxQL)

yes

SQL-92 is not fully supported

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

IDistributedCache
JCache
LINQ
Proprietary native API

Proprietary protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Proprietary protocol
Thrift

Supported programming languages

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

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

C++

Server-side scripts

Stored procedures

Java Stored Procedures

support for stored procedures with SQL-Server CLR

Triggers

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, with selectable consistency level

none

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
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

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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

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

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

NCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
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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

NCache Open Source is free on an as-is basis without any support. NCache Enterprise...
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