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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. 
Advice on Algolia and Manticore Search
Rana Usman Shahid
Chief Technology Officer at TechAvanza · | 6 upvotes · 396.6K views
Needs advice
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AlgoliaAlgoliaElasticsearchElasticsearch
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FirebaseFirebase

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!

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Replies (2)
Josh Dzielak
Co-Founder & CTO at Orbit · | 8 upvotes · 298K views
Recommends
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AlgoliaAlgolia

Hi Rana, good question! From my Firebase experience, 3 million records is not too big at all, as long as the cost is within reason for you. With Firebase you will be able to access the data from anywhere, including an android app, and implement fine-grained security with JSON rules. The real-time-ness works perfectly. As a fully managed database, Firebase really takes care of everything. The only thing to watch out for is if you need complex query patterns - Firestore (also in the Firebase family) can be a better fit there.

To answer question 2: the right answer will depend on what's most important to you. Algolia is like Firebase is that it is fully-managed, very easy to set up, and has great SDKs for Android. Algolia is really a full-stack search solution in this case, and it is easy to connect with your Firebase data. Bear in mind that Algolia does cost money, so you'll want to make sure the cost is okay for you, but you will save a lot of engineering time and never have to worry about scale. The search-as-you-type performance with Algolia is flawless, as that is a primary aspect of its design. Elasticsearch can store tons of data and has all the flexibility, is hosted for cheap by many cloud services, and has many users. If you haven't done a lot with search before, the learning curve is higher than Algolia for getting the results ranked properly, and there is another learning curve if you want to do the DevOps part yourself. Both are very good platforms for search, Algolia shines when buliding your app is the most important and you don't want to spend many engineering hours, Elasticsearch shines when you have a lot of data and don't mind learning how to run and optimize it.

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Mike Endale
Recommends
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Cloud FirestoreCloud Firestore

Rana - we use Cloud Firestore at our startup. It handles many million records without any issues. It provides you the same set of features that the Firebase Realtime Database provides on top of the indexing and security trims. The only thing to watch out for is to make sure your Cloud Functions have proper exception handling and there are no infinite loop in the code. This will be too costly if not caught quickly.

For search; Algolia is a great option, but cost is a real consideration. Indexing large number of records can be cost prohibitive for most projects. Elasticsearch is a solid alternative, but requires a little additional work to configure and maintain if you want to self-host.

Hope this helps.

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Pros of Algolia
Pros of Manticore Search
  • 126
    Ultra fast
  • 95
    Super easy to implement
  • 73
    Modern search engine
  • 71
    Excellent support
  • 70
    Easy setup, fast and relevant
  • 46
    Typos handling
  • 40
    Search analytics
  • 31
    Distributed Search Network
  • 31
    Designed to search records, not pages
  • 30
    Multiple datacenters
  • 10
    Smart Highlighting
  • 9
    Search as you type
  • 8
    Multi-attributes
  • 8
    Instantsearch.js
  • 6
    Super fast, easy to set up
  • 5
    Amazing uptime
  • 5
    Database search
  • 4
    Highly customizable
  • 4
    Great documentation
  • 4
    Github-awesome-autocomple
  • 4
    Realtime
  • 3
    Powerful Search
  • 3
    Places.js
  • 3
    Beautiful UI
  • 2
    Ok to use
  • 2
    Integrates with just about everything
  • 2
    Awesome aanltiycs and typos hnadling
  • 1
    Developer-friendly frontend libraries
  • 1
    Smooth platform
  • 1
    Fast response time
  • 1
    Github integration
  • 0
    Nooo
  • 0
    Fuck
  • 0
    Giitera
  • 0
    Is it fool
  • 2
    Easy to scale
  • 2
    Free
  • 2
    Distributed
  • 2
    Easy to get started
  • 2
    Real-time inserts
  • 2
    Lightweight
  • 2
    Open source
  • 2
    Low RAM consumption
  • 2
    JSON over HTTP
  • 2
    MySQL/PostgreSQL/ODBC/xml/csv sync out of the box
  • 2
    SQL syntax

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Cons of Algolia
Cons of Manticore Search
  • 11
    Expensive
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    What is 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.

    What is 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.

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      What are some alternatives to Algolia and Manticore Search?
      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 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.
      Swiftype
      Swiftype is the easiest way to add great search to your website or mobile application.
      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.
      Klevu
      It is an intelligent site search solution designed to help eCommerce businesses increase onsite sales and improve the customer online shopping experience.
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