Apache Solr is an open-source enterprise search server.
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IBM Watson Discovery
Score 9.1 out of 10
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IBM offers Watson Discovery, a natural language processing (NLP) application with options to measure sentiment, detect entities, semantic roles, and other concepts.
We tryed to promote Redis as cache solution for application, in order to replace Apache Solr, but it won't go well. Redis best pratices requires some more computer resources. With Elastic Search, the use case was another, and don't compete with Apache Solr.
We have considering AWS search and Elastic search but decide to go with Solr as we need high speed and flexible query, and so far it meets all our requirement so we still continue with Solr.
We tried to use both Elasticsearch and Swiftype with Drupal 8 but there are currently no good modules that integrate Drupal with those solutions. So Solr was really the only option for a Drupal 8 web site. It's not as easy to learn or use as Swiftype, but in the end I think it …
Before using Solr, we used a self-made search engine. Solr has helped us increase our capacity to serve our customers the results they are looking for easily without breaking down. Our previous platform was not dynamic enough to accommodate our growing traffic or smart enough …
Azure Search is not as mature as Apache Solr at this point. So the range of query flexibility is less than Solr. Also, when indexing content goes beyond 1 TB, it might become costly for Azure Search.
Between Solr and ElasticSearch, there is a constant struggle to pick the best one. ElasticSearch is part of ELK and ties in well with LogStash and Kibana which makes it great for logs and big data stuff. Add some logs and see which works best for your particular access methods …
We switched from search indexes stored in mysql to soar and it's made a world of difference for our growing businesses. The relational databases are very poor for handling the complex data searches require and Solr delivered all the tools we need to get the performance our end …
Apache Solr in general stacks up very well to its competitors, it provides much of the same features and performance and has the benefits of being an open-source project with an active contributor base that works consistently and improves the platform. Depending on your setup …
IBM Watson Discovery resulted more robust and performant, also the insights were much more interesting than just an AI search from Microsoft or a prompt for ChatGPT.
For starters, IBM Watson Discovery was very easy to use and set up. Google Cloud AI was more advanced in learning and navigating through it, in my opinion. Ironically, the free trial was the biggest selling point. We were trying on products, and it was faster to get started …
This is a unique application which provides automation comfortably and with the minimum of human interaction to create the perfect application for the client involved as generally there is a chance of someone else using the similar or slightly better tool
A edge of having a safe secure work environment where in organizations can make use of power of AI with no concern safe guard their data where IBM watson discovery provides hybrid cloud solution to mitigate the vulnerablity of data security.
To be entirely honest, in my review, I have used Elasticsearch in the past, but not in a way similar to that I am using Discovery, and I cannot honestly say that I can compare the two because I used Elasticsearch in infrastructure management and monitoring setup while using the …
Discovery differs from its competitors due to the better ease of implementation and the high level of natural language recognition, it is equal in integration resources such as API and workflow or process pipeline, but it loses in the price for a high volume of documents and/or …
In terms of performance, IBM Watson Discovery performs well and as expected compared to competitor offerings. Search works well Web crawl, content library creation, and 3rd party integration all possible The main driver for us is that we were already using other IBM …
IBM Watson Discovery for salesforce stacks up really well against the other products. It provides higher, better, and faster insight and capabilities than other options. We evaluated the return on investment and saw how great it would be to use for what we have. I think it has …
I have not found any other software solutions that can stack up against IBM Watson Discovery for Salesforce. This feature has proved nothing but beneficial for our bottom-line, as well as our customers'. I would recommend this solution to any company that heavily focuses on …
Very effective for end-user searching applications and for generating search results. Also very well suited to those looking for high reliability and performance. If [you're doing] fuzzy searching or if you are working on a smaller end-user application or an internal application that does not require high performance and flexible/adapting searching then it may not be necessary to use Solr.
Whether using it as a standalone search tool, integrating with other IBM Watson products, or using the API to integrate with proprietary or third-party systems and applications, Watson Discovery addresses these and many other scenarios where document search is required -- understand- if here documents can be pdf, doc, txt files, websites, among other formats --, don't confuse Watson Discovery with EDRMS (Electronic document and records management system) software, Discovery goes further, allowing text search to be done within a context using natural language (NLU) and returning not only the search term but also insights and related issues. File indexing works very well, and training Discovery so that documents and technical terms are learned a bit of work, but it can be reduced by using some of the learning models already trained and available for use.
Faceted navigation and field collapsing/grouping : filtering and quick results were what we needed for our websites. Our customers needed to have this functionalities for good and efficient results.
We tested them with our customers' registered searches (they received all new goods matching with their registered searches by emails and/or mobile push). Results were incredible by comparison with our old system (old MySQL requests).
Note : we didn't put all our data in Solr. Just what we need for searching uses. Other data stayed in our MySQL database.
Auto-suggest : our old auto-suggest wasn't performing well. With Apache Solr, our new one was worked really well ! The suggestions came quickly and suggestions were good.
We also extended auto-suggestion with geo-spatial data and it worked well.
Hit highlighting : we used this functionality and we didn't have problem and nasty surprise.
Keep all data status during data upgrading (see next details for improvements)
I believe AI should be more flexible about providing data. However, it's understandable that you need to provide the details you need in a more specific and detailed way.
The interface could use more tweaking. Being new to the program, it was kind of hard to navigate.
Luckily, there was a customized feature of the dashboard that I could set up, and having something that you know where you are placed always feels familiar and comfortable.
It takes some time to deploy and currectly maintein it. And also, to learn how to use and integrate in the enviroment as well. Once you get theses steps done, it usability is very simple, and almost of the time it don't require no further attention on it. Even for maintence, if you deploy it on a cluster mode, it is very reliable and easy to take one host down.
IBM Watson Discovery has the best user capabilities and easily transform business decision-making portfolio. The automation system saves time used in data analysis as opposed to manual research that consumes a lot of time. The visualization across the dashboard enables my team to interpret complex data and use it to make reliable marketing decisions.
Similar to all IBM Watson and Salesforce product solutions, the overall support would be a 10/10. Their provided FAQ's help with frequently experienced issues and if still unable to figure something out, their customer service representatives are always super responsive. With instant chat functions available, it is easy to ask a quick question rather than sitting on hold.
We switched from search indexes stored in MySQL to soar and it's made a world of difference for our growing businesses. The relational databases are very poor for handling the complex data searches require and Solr delivered all the tools we need to get the performance our end users are demanding.
To be entirely honest, in my review, I have used Elasticsearch in the past, but not in a way similar to that I am using Discovery, and I cannot honestly say that I can compare the two because I used Elasticsearch in infrastructure management and monitoring setup while using the ELK stack (Elasticsearch - Logstash and Kibana).
It's enabled us to deliver fast, relevant search results on our new website. The site is still in beta and being actively developed so our complete ROI is still unknown.
It integrates very well with Drupal so it has saved us from having to develop a custom solution.
IBM Watson Discovery has had only positive impacts on our overall business objective of providing quality customer service and timely resolutions for our clients.
The use of this integration has made life easier for our customer service team, who can now resolve cases for customers quicker and easier.
Our company prides itself on the service and expertise we're able to provide for our customers and IBM Watson Discovery has only made that task easier for our employees to perform.