From Coveo to Elasticsearch

Elastic Stack Elasticsearch
1

Dear Community,

I have a web application built for enterprise search using Coveo. It has lot of sources (CSVs, Excel, Sharepoint, S3, APIs, etc.) indexed using default Coveo Connectors and few custom Connector written in C#.

I wanted to build a POC for the same and be able to demonstrate the Elasticsearch Capabilities with all those sources.

Key Points:

  1. Data is not only incremental but also mutable. Meaning, already indexed data can have changes must be able to update the changes.

  2. I need a one technology to connect and index all those data sources. Be it python Client or Logstash. what is the best possibility. I do not have any logs for now.

  3. One of the main reasons to move to Elasticsearch is due to open source. whereas, Coveo needs License.

BTW, I am Elastic Certified Engineer, But I don't have good experience in font-end Stack. I am looking for advise from both front-end & Back-end perspective.

I really do appreciate your recommendations/ suggestions.

Thank you!

2

Welcome!

Why not using Elastic Workplace Search?

It's designed for that use case.

3

Hi @dadoonet

Thank you for your response.

I'm not sure I can go with that in actual project. I can cover some extent using basic version though.

so, just wanted to go with open source stack.

4

Up to you.

Note that Workplace Search is available in the free version with the built in basic license.

If you want to "re-implement" by yourself all the crawlers in a single tool and the UI, I'm not sure what advice I can give. As a Java developer, I'd probably go to the Java route but it's up to you.

For binary documents (PDF, etc) you can use the ingest attachment plugin.

There an example here: Using the Attachment Processor in a Pipeline | Elasticsearch Plugins and Integrations [7.10] | Elastic

PUT _ingest/pipeline/attachment
{
  "description" : "Extract attachment information",
  "processors" : [
    {
      "attachment" : {
        "field" : "data"
      }
    }
  ]
}
PUT my_index/_doc/my_id?pipeline=attachment
{
  "data": "e1xydGYxXGFuc2kNCkxvcmVtIGlwc3VtIGRvbG9yIHNpdCBhbWV0DQpccGFyIH0="
}
GET my_index/_doc/my_id

The data field is basically the BASE64 representation of your binary file.

You can use FSCrawler. There's a tutorial to help you getting started.

5

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