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  5. Algolia vs Manticore Search

Algolia vs Manticore Search

OverviewDecisionsComparisonAlternatives

Overview

Algolia
Algolia
Stacks1.4K
Followers1.1K
Votes699
Manticore Search
Manticore Search
Stacks10
Followers21
Votes22
GitHub Stars11.4K
Forks619

Algolia vs Manticore Search: What are the differences?

<Write Introduction here>

  1. Indexing Speed: Algolia has a faster initial indexing speed for small to medium-sized datasets compared to Manticore Search. This means that Algolia can quickly make data searchable in its system, making it a preferred choice for applications requiring real-time indexing updates.

  2. Query Flexibility: Manticore Search offers more advanced query capabilities and a wider range of search features compared to Algolia. This includes support for complex boolean queries, phrase matching, and proximity searches, making Manticore Search more suitable for applications with intricate search requirements.

  3. Scalability: Algolia provides a cloud-based search service that offers easy scalability for handling fluctuating search traffic and data volumes. In contrast, Manticore Search can be deployed on self-managed servers, giving users greater control over their infrastructure and allowing for more customizable scaling options based on specific needs.

  4. Customizability: Manticore Search allows for extensive customization of the search engine's behavior and functionalities through user-defined functions (UDFs) and plugins. On the other hand, Algolia offers a more streamlined setup with limited customization options, which may be sufficient for basic search needs but less effective for highly specialized requirements.

  5. Community Support: Manticore Search benefits from a more active open-source community, providing users with a broader range of resources, plugins, and community-developed extensions. Algolia, being a commercially focused service, may have more limited community-driven support options available to users.

  6. Price Structure: Algolia follows a SaaS pricing model based on usage metrics such as the number of records indexed and search operations performed. In contrast, Manticore Search is open-source software, allowing users to deploy it for free but incurring costs for additional features, support, and maintenance services as needed.

In Summary, Algolia excels in initial indexing speed and scalability, while Manticore Search offers more advanced query options, customization, and community support with a different pricing structure.

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Advice on Algolia, Manticore Search

Rana Usman
Rana Usman

Chief Technology Officer at TechAvanza

Jun 4, 2020

Needs adviceonFirebaseFirebaseElasticsearchElasticsearchAlgoliaAlgolia

Hey everybody! (1) I am developing an android application. I have data of around 3 million record (less than a TB). I want to save that data in the cloud. Which company provides the best cloud database services that would suit my scenario? It should be secured, long term useable, and provide better services. I decided to use Firebase Realtime database. Should I stick with Firebase or are there any other companies that provide a better service?

(2) I have the functionality of searching data in my app. Same data (less than a TB). Which search solution should I use in this case? I found Elasticsearch and Algolia search. It should be secure and fast. If any other company provides better services than these, please feel free to suggest them.

Thank you!

408k views408k
Comments

Detailed Comparison

Algolia
Algolia
Manticore Search
Manticore Search

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.

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.

Database search;Multi-attributes;Search as you type;Analytics dashboard; Ranking; Mobile; Search in any language;Understand users mistakes;Smart Highlighting;Realtime indexing;Protect your indexes from misuse;Discover realtime faceting;Search objects by location
Full-text searching; RealTIme indexing; Facets; Percolate Queries; Distributed indexes; JSON attributes
Statistics
GitHub Stars
-
GitHub Stars
11.4K
GitHub Forks
-
GitHub Forks
619
Stacks
1.4K
Stacks
10
Followers
1.1K
Followers
21
Votes
699
Votes
22
Pros & Cons
Pros
  • 126
    Ultra fast
  • 95
    Super easy to implement
  • 73
    Modern search engine
  • 71
    Excellent support
  • 70
    Easy setup, fast and relevant
Cons
  • 11
    Expensive
Pros
  • 2
    Easy to get started
  • 2
    Free
  • 2
    MySQL/PostgreSQL/ODBC/xml/csv sync out of the box
  • 2
    Low RAM consumption
  • 2
    Open source
Integrations
React
React
Ruby
Ruby
Jekyll
Jekyll
JavaScript
JavaScript
React Native
React Native
Vue.js
Vue.js
WordPress
WordPress
Shopify
Shopify
Docusaurus
Docusaurus
VuePress
VuePress
No integrations available

What are some alternatives to Algolia, Manticore Search?

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).

Solr

Solr

Solr is the popular, blazing fast open source enterprise search platform from the Apache Lucene project. Its major features include powerful full-text search, hit highlighting, faceted search, near real-time indexing, dynamic clustering, database integration, rich document (e.g., Word, PDF) handling, and geospatial search. Solr is highly reliable, scalable and fault tolerant, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more. Solr powers the search and navigation features of many of the world's largest internet sites.

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.

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.

Swiftype

Swiftype

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

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.

Dejavu

Dejavu

dejaVu fits the unmet need of being a hackable data browser for Elasticsearch. Existing browsers were either built with a legacy UI and had a lacking user experience or used server side rendering (I am looking at you, Kibana).

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