Wednesday, February 20, 2013

Government Must Support Open Source Foundations - Tired Of Google Monopoly - Support The Free Open Source Search Engines - No Ads, No Spam, No Stupid Suggestions - Demand Google To Become Fully Open Source And Free For Everyone - Right To Education Is A Basic Human Right - Join The Revolution Of Big Genius Ideas :)

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ElasticSearch is a distributed, RESTful, free/open source search server based on Apache Lucene. It is developed by Shay Banon[1] and is released under the terms of the Apache License. ElasticSearch is developed in Java.



Shay Banon created Compass in 2004.[2] While thinking about the third version of Compass he realized that it would be necessary to rewrite big parts of Compass to "create a scalable search solution".[2] So he created "a solution built from the ground up to be distributed" and used a common interface, JSON over HTTP, suitable for programming languages other than Java as well.[2] Shay Banon released the first version of ElasticSearch in February 2010.[3]
In a French interview some more ideas are explained.[4]


ElasticSearch can be used to search all kinds of documents. It provides a scalable search solution, has near real-time search and support for multitenancy.[5] "ElasticSearch is distributed, which means that indices can be divided into shards and each shard can have zero or more replicas. Each node hosts one or more shards, and acts as a coordinator to delegate operations to the correct shard(s). Rebalancing and routing are done automatically [...]".[5]
It uses Apache Lucene and tries to make all features of it available through the JSON and Java API. It supports facetting and percolating, which can be useful for notifying if new documents match for registered queries.
Another feature is called 'Gateway' and handles the long term persistence of the index[6]- i.e. an index can be recovered from the Gateway in a case of a server crash. ElasticSearch supports real-time GET requests, which makes it suitable as a NoSQL solution,[7] but it lacks distributed transactions.[8]

Comparison to other software

Apache Solr is another open source search server built on top of Apache Lucene. There are some documents comparing features or performance of Apache Solr and ElasticSearch. Sematext published a series of posts starting with Solr vs. ElasticSearch Overview[9] comparing ElasticSearch vs. Solr (Solr 4.0, aka SolrCloud, more specifically) in the most comprehensive and neutral comparison to date. In an article from Ryan Sonnek it will be pointed out how Apache Solr and ElasticSearch compare regarding near real-time indexing and searching.[10]
An article in the German iX magazine from Peter Karich lists advantages and disadvantages of ElasticSearch [11] - an English slide is also available,[12] which can be summarized as follows:
  • ElasticSearch is distributed. No separate project required. Replicas are near real-time too, which is called "Push replication".[13][14]
  • ElasticSearch fully supports the near real-time search of Apache Lucene.
  • Handling multitenancy is not a special configuration, whereas a more advanced setup is necessary with Solr.
  • ElasticSearch introduces the concept of the Gateway,[6] which makes full backups easier.
  • Only one main developer.[1] This can be mitigated since there is now the company ElasticSearch where not only one man is involved.
Different Usage
  • Use parent/child feature instead of Solr's results grouping or have a look into this issue .
  • No XML support, only JSON
  • Common container deployment (as a WAR file) is in development plugin
  • No convenient wrapper for Java beans as the @Field annotation in SolrJ


There are already smaller and some bigger companies using ElasticSearch,[15] including StumbleUpon,[16] Mozilla [17][18] and Github.[19]


See also

With Proquest Udini, we have created the worlds largest online article store, and aim to be the center for researchers all over the world. We connect to a 700M solr cluster for search, but have recently also implemented a search component with ElasticSearch. We will discuss how we did this, and how we want to use the 30M index for scientific citation recognition. We will highlight lessons learned in integrating ElasticSearch in our virtualized EC2 environments, and challenges aligning with our continuous deployment processes.



In this session we will explore elasticsearch, specifically, how to handle huge amount of data with it, how to effectively search it, and last, use facets to derive complex, (near) real time analytics from it.


Summary: Elasticsearch’s Series B round of funding shows continuing interest among easy-to-use, open-source big-data analytics tools. The funding also heats up the competition for a market leader.
Open-source search provider Elasticsearch has secured $24 million in Series B venture funding, showing business demand for free and simple big-data analytics. Mike Volpi of Index Ventures led the funding round, which included contributions from Benchmark Capital and SV Angel.

Amsterdam-based Elasticsearch, which has now raised a total of $34 million, generates revenue by teaching people how to use the tool at training courses and help them solve problems by way of support

subscriptions. Introduced in 2010 after founder Shay Banon developed it in his free time, the open-source Elasticsearch program today gets downloaded 200,000 times a month. Banon launched the company itself six months ago, when CEO Steven Schuurman got involved, in time to take on a Series A round.

Elasticsearch can make quick work of searching billions of documents and petabytes of data, structured and unstructured alike, said Banon, now the company’s chief technology officer. A single developer can use it to find needles amid haystacks of tweets and other kinds of data, eliminating the need for a team of data scientists, Banon said.

Like LucidWorks, Elasticsearch was developed on top of open-source Apache Lucene. But LucidWorks (which until August 2012 was named Lucid Imagination and has raised at least $16 million) focuses more on the enterprise, as my colleague Barb Darrow has reported, while Elasticsearch has caught on with startups and enterprises alike in several industries, according to Schuurman.


This is a list of articles about search engines, including web search engines, selection-based search engines, metasearch engines, desktop search tools, and web portals and vertical market websites that have a search facility for online databases.

Alternatives to Google. Various search engines that you can use instead of Google, with some interesting sites like Google that are useful to know about.
top alternatives to google, open source search engines, search by your demands

For a text version of this video, as well as links to the various search engines, visit:


By content/topic


P2P search engines

Metasearch engines

Geographically limited scope











Real estate / property


Video Games

By information type

Search engines dedicated to a specific kind of information




Source code


These search engines work across the BitTorrent protocol.

Search Here:


Search engines listed below find various types of files that have been stored in the cloud and made publicly available.




Question and answer

Human answers

Automatic answers

Natural language

By model

Privacy search engines

Open source search engines

Semantic browsing engines

Social search engines

Visual search engines

Search appliances

Desktop search engines

Name Platform Remarks License
Autonomy Windows IDOL Enterprise Desktop Search. Proprietary, commercial
Beagle Linux Open source desktop search tool for Linux based on Lucene. Unmaintained since 2009. A mix of the X11/MIT License and the Apache License
Copernic Desktop Search Windows
Free for home use
Docfetcher Cross-platform Open source desktop search tool for Windows and Linux, based on Apache Lucene Eclipse Public License
dtSearch Desktop Windows
Proprietary (30 day trial)
Easyfind Mac OS
Everything Windows Find files and folders by name instantly on NTFS volumes Freeware
Google Desktop Linux, Mac OS, Windows Integrates with the main Google search engine page. 5.9 Release now supports x64 systems. As of September 14, 2011, Google has discontinued this product. Freeware
GNOME Storage Linux Open Source desktop search tool for Unix/Linux GPL
imgSeek Linux, Mac OS, Windows Desktop content-based image search GPL v2 [1]
InSight Desktop Search Windows Metadata-based search utility Freeware
ISYS Search Software Windows ISYS:desktop search software. Proprietary (14 day trial)
Locate32 Windows Graphical port of Unix's locate & updatedb BSD License[2]
Lookeen Windows Outlook Search Tool, with integrated Desktop Search Proprietary (14 day trial)
Meta Tracker Linux, Unix Open Source desktop search tool for Unix/Linux GPL v2 [3]
Recoll Linux, Unix Open Source desktop search tool for Unix/Linux GPL [4]
Spotlight Mac OS Found in Apple Mac OS X "Tiger" and later OS X releases. Proprietary
Strigi Linux, Unix, Solaris, Mac OS X and Windows Cross-platform open source desktop search engine LGPL v2 [5]
Terrier Search Engine Linux, Mac OS, Unix Desktop search for Windows, Mac OS X (Tiger), Unix/Linux. MPL
Tropes Zoom Windows Semantic Search Engine. Freeware and commercial
Windows Search Windows Part of Windows Vista and later OSs. Available as Windows Desktop Search for Windows XP and Server 2003. Does not support indexing UNC paths on x64 systems. Proprietary, freeware


Based on




Defunct or acquired search engines

See also


  1. ^ According to COPYING in SVN trunk on SourceForge.
  2. ^ According to
  3. ^ According to COPYING in SVN trunk.
  4. ^ According to [1].
  5. ^ According to COPYING in version 0.5.10 tar.bz2 package.

External links



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