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Algolia vs Typesense: What are the differences?

Introduction

In this Markdown code, I will provide the key differences between Algolia and Typesense.

  1. Data Scalability: Algolia is a search-as-a-service platform that offers high scalability, allowing businesses to handle millions of queries per second across a large dataset. On the other hand, Typesense is a lightweight search engine that is designed to handle smaller datasets and lower query volumes.

  2. Focused Use Case: Algolia is ideal for complex search use cases that require advanced features such as faceting, filtering, and typo-tolerance. It provides various customizable options for search relevance and ranking. On the contrary, Typesense is designed for simpler search requirements, focusing on delivering instant search results without the need for extensive configurations or customizations.

  3. Ease of Deployment: Algolia offers a fully-hosted solution where businesses can use Algolia's infrastructure to power their search functionality. This eliminates the need for setting up and maintaining search servers. In contrast, Typesense can be self-hosted, allowing businesses to have more control over their search infrastructure and data.

  4. Query Performance: Algolia prioritizes fast response times, aiming for sub-50ms latency for search queries. It achieves this by optimizing the search infrastructure and leveraging distributed systems. Typesense also aims for low latency but may have slightly higher response times compared to Algolia due to its lightweight nature.

  5. Pricing Model: Algolia follows a usage-based pricing model, where businesses are billed based on the number of operations performed, including the number of indexed records and search queries. Typesense, on the other hand, offers a fixed pricing model based on the number of nodes in the cluster, regardless of the number of records or search queries.

  6. Community and Ecosystem: Algolia has a larger and more mature community, which means there are more resources, libraries, and integrations available. It also has better documentation and support options. Typesense is relatively newer and may have a smaller community and less extensive ecosystem, although it is growing rapidly.

In Summary, the key differences between Algolia and Typesense lie in their scalability, use cases, deployment options, query performance, pricing model, and community/ecosystem size.

Advice on Algolia and Typesense
Rana Usman Shahid
Chief Technology Officer at TechAvanza · | 6 upvotes · 376.8K views
Needs advice
on
AlgoliaAlgoliaElasticsearchElasticsearch
and
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 · 280.9K views
Recommends
on
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
on
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 Typesense
  • 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
    Designed to search records, not pages
  • 30
    Distributed Search Network
  • 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
    Database search
  • 5
    Amazing uptime
  • 4
    Realtime
  • 4
    Github-awesome-autocomple
  • 4
    Great documentation
  • 4
    Highly customizable
  • 3
    Beautiful UI
  • 3
    Powerful Search
  • 3
    Places.js
  • 2
    Awesome aanltiycs and typos hnadling
  • 2
    Integrates with just about everything
  • 1
    Developer-friendly frontend libraries
  • 1
    Ok to use
  • 1
    Fast response time
  • 1
    Github integration
  • 1
    Smooth platform
  • 0
    Fuck
  • 0
    Giitera
  • 0
    Is it fool
  • 0
    Nooo
  • 5
    Free
  • 4
    Facet search
  • 4
    Easy to deploy
  • 3
    Out-of-the-box dev experience
  • 3
    Ultra fast
  • 3
    Search as you type
  • 3
    Typo handling
  • 3
    Open source
  • 2
    Near real-time search
  • 2
    Super easy to implement
  • 2
    InstantSearch integration
  • 2
    Modern search engine
  • 1
    Restful
  • 1
    Great documentation
  • 1
    SaaS option

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Cons of Algolia
Cons of Typesense
  • 11
    Expensive
    Be the first to leave a con

    Sign up to add or upvote consMake informed product decisions

    - No public GitHub repository available -

    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 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.

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    What are some alternatives to Algolia and Typesense?
    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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