Solution to build a quick web-based documents search engine

Question

I'm trying to assess the feasibility of quickly building a web-based search engine to support search through roughly 10000 files (mostly PDF, MS Word and Excel). Since this would be a temporary solution used by a handful of users, it would have to rely on free open-source software, and should require minimal deployment time.

• A search engine indexing all file formats in scope, and providing NLP-capable search (lemmatization, stemming...). I'm thinking Solr here
• A web-interface, that can be deployed with zero code
• Easy-to-deploy packages, such as Docker containers
• Capable of working on one or two servers only. No high-availability is required.
• Based on free open-source software

Would anyone have suggestions on possible solutions?

Answer 1

You can use a standard Document Management Systems here.

As an example I know (no endorsement): For TYPO3 CMS you can use the built-in search "indexed_search", or you can install various plugins for external search providers (e.g. a TYPO3 extension for SOLR). For indexed-search on Linux, it is required that you install the respective 3rd-party commandline tools for indexing text files. For PDFs that would be pdftools, for WORD catdog, for zipfiles unzip, for Excel xlhtml.

These CMSs often have Docker-based images available, built by the vendors or by enthusiastic community members.

I think other CMSs such as Wordpress or Drupal have similar solutions.

There is much to learn though. Also do you have a requirements that logged-in users should see more search results than normal public users. That will complicate things.

Answer 2

Alfresco ingests your documents (MS Office, LibrerOffice, PDF, text, etc), indexes them using Solr, and lets you search using a web interface.

It is free and open source (GPLv3 license), downloadable as Docker images.

It easily runs on a single machine. No coding needed.

Out-of-the-box it uses a file-based database which is not very powerful (but should be enough for 10000 documents). If you need more performance, you can select your own database (such as MariaDB or PostGreSQL) when installing.