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  4. Search As A Service
  5. Swiftype vs rasa NLU

Swiftype vs rasa NLU

OverviewComparisonAlternatives

Overview

Swiftype
Swiftype
Stacks192
Followers96
Votes11
rasa NLU
rasa NLU
Stacks120
Followers282
Votes25

rasa NLU vs Swiftype: What are the differences?

Developers describe rasa NLU as "Open source, drop-in replacement for NLP tools like wit.ai". rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries. On the other hand, Swiftype is detailed as "Powerful and scalable search for any application or website". Swiftype is the easiest way to add great search to your website or mobile application.

rasa NLU belongs to "NLP / Sentiment Analysis" category of the tech stack, while Swiftype can be primarily classified under "Search as a Service".

Some of the features offered by rasa NLU are:

  • open source
  • python
  • NLP

On the other hand, Swiftype provides the following key features:

  • Quick Start- Install by pasting a JavaScript snippet in your page.
  • Autocomplete- our search engines come with autocomplete built-in
  • Detailed Analytics- Our built-in search analytics give you real-time insight into what your users are looking for.

rasa NLU is an open source tool with 5.77K GitHub stars and 1.7K GitHub forks. Here's a link to rasa NLU's open source repository on GitHub.

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Detailed Comparison

Swiftype
Swiftype
rasa NLU
rasa NLU

Swiftype is the easiest way to add great search to your website or mobile application.

rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.

Quick Start- Install by pasting a JavaScript snippet in your page.;Autocomplete- our search engines come with autocomplete built-in;Detailed Analytics- Our built-in search analytics give you real-time insight into what your users are looking for.;Custom Result Ranking- Drag-and-drop results to re-order them.;VIP-approved WordPress search plugin- Just install the plugin and your ready to go.;Great Mobile Support- Our search works great in mobile browsers, and our native iOS and Android SDKs make app integration a breeze.;Advanced Developer API- Our Developer API gives you low-level access to our search technology.
Open source; NLP; Machine learning
Statistics
Stacks
192
Stacks
120
Followers
96
Followers
282
Votes
11
Votes
25
Pros & Cons
Pros
  • 8
    Very easy setup and highly customizable for your search
  • 1
    Analytics
  • 1
    Role devision to develop, design, manage
  • 1
    Easy setup
Cons
  • 1
    Expensive
  • 1
    API Calls Monitoring/Alerts
  • 1
    Cost Prediction
  • 1
    Customer Support
Pros
  • 9
    Open Source
  • 6
    Self Hosted
  • 6
    Docker Image
  • 3
    Comes with rasa_core
  • 1
    Enterprise Ready
Cons
  • 4
    No interface provided
  • 4
    Wdfsdf
Integrations
No integrations available
Slack
Slack
RocketChat
RocketChat
Google Hangouts Chat
Google Hangouts Chat
Telegram
Telegram
Microsoft Bot Framework
Microsoft Bot Framework
Twilio
Twilio
Mattermost
Mattermost

What are some alternatives to Swiftype, rasa NLU?

Elasticsearch

Elasticsearch

Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).

Algolia

Algolia

Our mission is to make you a search expert. Push data to our API to make it searchable in real time. Build your dream front end with one of our web or mobile UI libraries. Tune relevance and get analytics right from your dashboard.

Typesense

Typesense

It is an open source, typo tolerant search engine that delivers fast and relevant results out-of-the-box. has been built from scratch to offer a delightful, out-of-the-box search experience. From instant search to autosuggest, to faceted search, it has got you covered.

Amazon CloudSearch

Amazon CloudSearch

Amazon CloudSearch enables you to search large collections of data such as web pages, document files, forum posts, or product information. With a few clicks in the AWS Management Console, you can create a search domain, upload the data you want to make searchable to Amazon CloudSearch, and the search service automatically provisions the required technology resources and deploys a highly tuned search index.

Amazon Elasticsearch Service

Amazon Elasticsearch Service

Amazon Elasticsearch Service is a fully managed service that makes it easy for you to deploy, secure, and operate Elasticsearch at scale with zero down time.

Manticore Search

Manticore Search

It is a full-text search engine written in C++ and a fork of Sphinx Search. It's designed to be simple to use, light and fast, while allowing advanced full-text searching. Connectivity is provided via a MySQL compatible protocol or HTTP, making it easy to integrate.

Azure Search

Azure Search

Azure Search makes it easy to add powerful and sophisticated search capabilities to your website or application. Quickly and easily tune search results and construct rich, fine-tuned ranking models to tie search results to business goals. Reliable throughput and storage provide fast search indexing and querying to support time-sensitive search scenarios.

SpaCy

SpaCy

It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.

MeiliSearch

MeiliSearch

It is a powerful, fast, open-source, easy to use, and deploy search engine. The search and indexation are fully customizable and handles features like typo-tolerance, filters, and synonyms.

Quickwit

Quickwit

It is the next-gen search & analytics engine built for logs. It is designed from the ground up to offer cost-efficiency and high reliability on large data sets. Its benefits are most apparent in multi-tenancy or multi-index settings.

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