DBMS > Amazon DynamoDB vs. Cubrid vs. Firebird vs. NCache vs. Sphinx

System Properties Comparison Amazon DynamoDB vs. Cubrid vs. Firebird vs. NCache vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

Firebird is an open source RDBMS forked from Borland's InterBase

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

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

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store

Search engine

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

aws.amazon.com/dynamodb

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

www.firebirdsql.org

www.alachisoft.com/ncache

sphinxsearch.com

Technical documentation

docs.aws.amazon.com/dynamodb

cubrid.org/manuals

www.firebirdsql.org/en/reference-manuals

www.alachisoft.com/resources/docs

sphinxsearch.com/docs

Developer

Amazon

CUBRID Corporation, CUBRID Foundation

Firebird Foundation

Alachisoft

Sphinx Technologies Inc.

Initial release

2012

2008

2000

As fork of Borland's InterBase

2005

2001

Current release

11.0, January 2021

5.0.0, January 2024

5.3.3, April 2024

3.5.1, February 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

Open Source

Initial Developer's Public License

Open Source

Enterprise Edition available

Open Source

GPL version 2, commercial licence available

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

C and C++

C#, .NET, .NET Core, Java

C++

Server operating systems

hosted

Linux
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

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

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

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)

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

IDistributedCache
JCache
LINQ
Proprietary native API

Proprietary protocol

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
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

Server-side scripts

Stored procedures

Java Stored Procedures

PSQL

support for stored procedures with SQL-Server CLR

Triggers

yes

by integration with AWS Lambda

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

optimistic locking and pessimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

yes

Durability

Support for making data persistent

yes

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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

More information provided by the system vendor

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Typical application scenarios

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