DBMS > MonetDB vs. NSDb vs. OrigoDB vs. Sphinx

System Properties Comparison MonetDB vs. NSDb vs. OrigoDB vs. Sphinx

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A relational database management system that stores data in columns

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A fully ACID in-memory object graph database

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

Primary database model

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

Search engine

Secondary database models

Document store
Spatial DBMS

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

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

Technical documentation

www.monetdb.org/Documentation

nsdb.io/Architecture

origodb.com/docs

sphinxsearch.com/docs

Developer

MonetDB BV

Robert Friberg et al

Sphinx Technologies Inc.

Initial release

2004

2017

2009

under the name LiveDB

2001

Current release

Dec2023 (11.49), December 2023

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Mozilla Public License 2.0

Open Source

Apache Version 2.0

Open Source

GPL version 2, commercial licence available

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

Java, Scala

C++

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS

Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

all fields are automatically indexed

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL 2003 with some extensions

SQL-like query language

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

Proprietary protocol

Supported programming languages

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

Java
Scala

.Net

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes, in SQL, C, R

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding via remote tables

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

yes

depending on model

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

Using Apache Lucene

yes

Write ahead log

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

fine grained access rights according to SQL-standard

Role based authorization

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

show all

Recent citations in the news

MonetDB Foundation launched
31 January 2024, Centrum Wiskunde & Informatica (CWI)

PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R — Part I
6 April 2018, Data Science Central

How MonetDB/X100 Exploits Modern CPU Performance
14 January 2020, Towards Data Science

Test of Time Award for paper on vectorized execution
16 January 2024, Centrum Wiskunde & Informatica (CWI)

Monet DB The Column-Store Pioneer
4 September 2019, Open Source For You

provided by Google News

Switching From Sphinx to MkDocs Documentation — What Did I Gain and Lose?
2 February 2024, Towards Data Science

Manticore is a Faster Alternative to Elasticsearch in C++
25 July 2022, hackernoon.com

Beyond the Concert Hall: 5 Organizations Making a Difference in Classical Music in 2018
22 December 2018, WQXR Radio

Here’s Why Russia Is Cracking Down on Google
23 February 2015, TIME

The Pirate Bay was recently down for over a week due to a DDoS attack
29 October 2019, The Hacker News

provided by Google News

Share this page