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Algolia vs MeiliSearch: What are the differences?
Introduction
Algolia and MeiliSearch are both search engines that allow developers to integrate powerful search capabilities into their applications. While they serve a similar purpose, there are key differences between the two that set them apart. Here, we will explore six specific differences between Algolia and MeiliSearch.
Hosting Options: Algolia offers a hosted solution, where the search engine is fully managed and hosted on their infrastructure. This relieves the developer from the operational and maintenance tasks associated with the search engine. On the other hand, MeiliSearch is a self-hosted search engine, which means developers have to set up and manage their own infrastructure to run and maintain MeiliSearch.
Data Indexing: Algolia uses an incremental indexing approach, where data is indexed in real-time as it is added or updated. This ensures that search results are always up to date, giving users the most relevant results. MeiliSearch, on the other hand, uses a batch indexing approach, where data needs to be indexed in batches. This can result in a slight delay in search results being updated with new or modified data.
Scalability: Algolia has been designed to handle high amounts of traffic and large datasets. With its distributed architecture and ability to automatically scale, Algolia can handle millions of queries per second and billions of records. MeiliSearch, while being a performant search engine, is more suitable for smaller applications and datasets as it may not handle extremely high traffic or large datasets as efficiently as Algolia.
Search Features: Algolia offers a wide range of powerful search features out-of-the-box, including typo tolerance, faceting, filtering, and personalization. These features are highly configurable and allow developers to fine-tune the search experience for their users. MeiliSearch, on the other hand, provides a simplified search experience and doesn't offer as many advanced search features by default. However, it does provide the flexibility for developers to implement custom search features.
Language Support: Algolia has extensive language support and offers features like language-specific stopwords and synonyms. This makes it easy to build multilingual search experiences that are optimized for different languages. MeiliSearch, while supporting multiple languages, does not offer as many language-specific features out-of-the-box as Algolia.
Community and Ecosystem: Algolia has an active and supportive community, with a wide range of resources and documentation available. It also has integrations with popular frameworks and libraries, making it easier for developers to integrate Algolia into their applications. MeiliSearch, while gaining popularity, has a smaller community and ecosystem compared to Algolia, which means there may be fewer resources and integrations available.
In summary, Algolia provides a fully managed, scalable, and feature-rich search engine that is suitable for large-scale applications, while MeiliSearch offers a more lightweight and customizable search engine that is well-suited for smaller applications.
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!
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.
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.
Pros of Algolia
- Ultra fast126
- Super easy to implement95
- Modern search engine73
- Excellent support71
- Easy setup, fast and relevant70
- Typos handling46
- Search analytics40
- Distributed Search Network31
- Designed to search records, not pages31
- Multiple datacenters30
- Smart Highlighting10
- Search as you type9
- Multi-attributes8
- Instantsearch.js8
- Super fast, easy to set up6
- Amazing uptime5
- Database search5
- Highly customizable4
- Great documentation4
- Github-awesome-autocomple4
- Realtime4
- Powerful Search3
- Places.js3
- Beautiful UI3
- Ok to use2
- Integrates with just about everything2
- Awesome aanltiycs and typos hnadling2
- Developer-friendly frontend libraries1
- Smooth platform1
- Fast response time1
- Github integration1
- Nooo0
- Fuck0
- Giitera0
- Is it fool0
Pros of MeiliSearch
- Saas option1
- Restfull1
- Open source1
- Typo handling1
- Search as you type1
- Useful defaults1
- Easy to deploy1
- Facet search1
- Great long tail search results1
- Fast responses to online chat1
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Cons of Algolia
- Expensive11