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MongoDB VS Meilisearch

Compare MongoDB VS Meilisearch and see what are their differences

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MongoDB logo MongoDB

MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

Meilisearch logo Meilisearch

Ultra relevant, instant, and typo-tolerant full-text search API
  • MongoDB Landing page
    Landing page //
    2023-10-21
  • Meilisearch Landing page
    Landing page //
    2023-12-16

Meilisearch 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.

MongoDB features and specs

  • Scalability
    MongoDB offers horizontal scaling through sharding, allowing it to handle large volumes of data and enabling distributed computing.
  • Flexible Schema
    It allows for a flexible schema design using BSON (Binary JSON), making it easier to iterate and change application data models.
  • High Performance
    MongoDB is optimized for read and write throughput, making it suitable for real-time applications.
  • Rich Query Language
    Supports a rich and expressive query language that allows for efficient querying and analytics.
  • Built-in Replication
    Provides robust replication mechanisms for high availability and redundancy.
  • Geospatial Indexing
    Offers powerful geospatial indexing capabilities, useful for location-based applications.
  • Aggregation Framework
    Enables complex data manipulations and transformations using the aggregation pipeline framework.
  • Cross-Platform
    Works on multiple operating systems, enhancing its versatility and deployment options.

Possible disadvantages of MongoDB

  • Memory Usage
    MongoDB can consume a large amount of memory due to its use of memory-mapped files, which may be a concern for some applications.
  • Complex Transactions
    While MongoDB supports ACID transactions, they can be more complex to implement and less efficient compared to traditional relational databases.
  • Data Redundancy
    The flexible schema design can lead to data redundancy and increased storage costs if not managed carefully.
  • Limited Joins
    Joins are supported but can be less efficient and more limited compared to relational databases, affecting complex relational data querying.
  • Indexing Overhead
    Extensive indexing can introduce overhead and impact performance, especially during write operations.
  • Learning Curve
    Requires a different mindset and understanding compared to traditional relational databases, which can present a learning curve for new users.
  • Lacks Mature Analytical Tools
    The ecosystem for analytical tools around MongoDB is not as mature as those for traditional relational databases, which might limit advanced analytics capabilities.
  • Cost
    The cost of using MongoDB's cloud services (MongoDB Atlas) can be high, especially for large-scale deployments.

Meilisearch features and specs

  • Speed
    Meilisearch is optimized for performance and provides very fast search capabilities, often with response times in milliseconds.
  • Relevance
    It offers advanced search features like typo tolerance, synonyms, and configurable ranking rules to ensure highly relevant search results.
  • Ease of Use
    Designed to be user-friendly with a straightforward RESTful API, making it easy to integrate and use.
  • Open Source
    Meilisearch is open source, allowing developers to inspect the code, contribute, and customize it to fit their own needs.
  • Language Support
    It supports multiple languages, ensuring effective full-text search capabilities in various linguistic contexts.
  • Lightweight
    Meilisearch is lightweight and can be deployed on modest hardware, making it suitable for small to medium-sized projects.
  • Real-time Indexing
    It offers real-time indexing, allowing the index to be updated without significant downtime or delay.

Possible disadvantages of Meilisearch

  • Maturity
    As a relatively young project, it may lack some advanced features and optimizations found in more established search solutions like Elasticsearch.
  • Ecosystem
    The ecosystem and community around Meilisearch are still growing, so you might find fewer plugins, extensions, and third-party tools compared to more mature solutions.
  • Scalability
    While suitable for small to medium projects, it might not be as scalable for very large datasets or highly complex queries compared to other search engines like Solr or Elasticsearch.
  • Complex Query Handling
    Meilisearch focuses on simplicity, which means it may lack some of the advanced query capabilities provided by more complex search engines.
  • Documentation
    Though improving, the documentation may not be as comprehensive as that of longer-established projects, which could lead to a steeper learning curve for some users.

MongoDB videos

+ Add

MySQL vs MongoDB

More videos:

  • Review - The Good and Bad of MongoDB
  • Review - what is mongoDB

Meilisearch videos

No Meilisearch videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to MongoDB and Meilisearch)

MongoDB

Meilisearch

Databases
93 93%
Databases
7% 7
Custom Search Engine
0 0%
Custom Search Engine
100% 100
NoSQL Databases
100 100%
NoSQL Databases
0% 0
Search Engine
0 0%
Search Engine
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare MongoDB and Meilisearch

MongoDB Reviews

10 Top Firebase Alternatives to Ignite Your Development in 2024
MongoDB’s superpower lies in its flexibility. Its document-based model lets you store data in a free-form, schema-less way, making it adaptable to evolving application needs. Need to add a new field or change the structure of your data? No problem, MongoDB handles it with ease.
Source: genezio.com
Top 7 Firebase Alternatives for App Development in 2024
MongoDB Realm provides a robust alternative to Firebase, especially for apps requiring a flexible data model. Key features include:
Source: signoz.io
Announcing FerretDB 1.0 GA - a truly Open Source MongoDB alternative
MongoDB is no longer open source. We want to bring MongoDB database workloads back to its open source roots. We are enabling PostgreSQL and other database backends to run MongoDB workloads, retaining the opportunities provided by the existing ecosystem around MongoDB.
Source: blog.ferretdb.io
16 Top Big Data Analytics Tools You Should Know About
The database added a new feature to its list of attributes called MongoDB Atlas. It is a global cloud database technology that allows to deploy a fully managed MongoDB across AWS, Google Cloud, and Azure with its built-in automation for resource, workload optimization and to reduce the time required to handle the database.
Source: www.analytixlabs.co.in
9 Best MongoDB alternatives in 2019
MongoDB is an open source NoSQL DBMS which uses a document-oriented database model. It supports various forms of data. However, in MongoDB data consumption is high due to de-normalization.
Source: www.guru99.com

Meilisearch Reviews

5 Open-Source Search Engines For your Website
MeiliSearch is an open-source, blazingly fast and hyper-relevant search engine that will improve your search experience. It provides an extensive toolset for customization. It works out-of-the-box with a preset that easily answers the needs of most applications. Communication is done with a RESTful API because most developers are already familiar with its norms.
Source: vishnuch.tech
MeiliSearch: Zero-config alternative to Elasticsearch, made in Rust | Hacker News
"We send events to our Amplitude instance to be aware of the number of people who use MeiliSearch. We only send the platform on which the server runs once by day. No other information is sent. If you do not want us to send events, you can disable these analytics by using the MEILI_NO_ANALYTICS env variable."
Source: news.ycombinator.com
Recommendations for Poor Man's ElasticSearch on AWS?
I'd second these two. I've been following them for quite some time. I even did an extensive research on which one I'd use, and I ended up with Typesense. I don't remember the specific reasoning though. Both seem quite good. MeiliSearch is written in Rust, which makes it more "hipsterish" ;)
Source: www.indiehackers.com

Social recommendations and mentions

Based on our record, MongoDB should be more popular than Meilisearch. It has been mentiond 18 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

MongoDB mentions (18)

  • Creating AI Memories using Rig & MongoDB
    In this article, we’ll build a CLI tool using the Rig AI framework and MongoDB for retrieval-augmented generation (RAG). This tool will store summarized conversations in a database and retrieve them when needed, enabling the AI to maintain context over time. - Source: dev.to / about 2 months ago
  • The Adventures of Blink S2e2: Database, Contained
    Have a Mongo database holding the various phrases we're going to use and potentially configuration data for the frontend as well. - Source: dev.to / 9 months ago
  • Introducing Perseid: The Product-oriented JS framework
    It's also worth mentioning that Perseid provides out-of-the-box support for React, VueJS, Svelte, MongoDB, MySQL, PostgreSQL, Express and Fastify. - Source: dev.to / 8 months ago
  • DocumentDB Elastic Cluster Pricing
    Does anyone know if the most basic Elastic Cluster instance of DocumentDB carries any monthly fixed cost or is it just on-demand cost? Another words if I run like 10,000 queries against the DB per month, what kind of bill would I expect? This is for a super small app. I am currently using mongodb free tier , but want to migrate everything to AWS. Can't seem to find a straight answer to the pricing question. Source: over 2 years ago
  • I wrote some scripts for converting the UTZOO Usenet archive to a Mongo Database
    You can use either MongoDB.com's dashboard (if you host a remote database) or Mongo Compass to run queries on the data or you can modify the express middleware with your own queries. I'm still working on the API, so it's not very robust yet. I will update this when it is. Source: over 2 years ago
View more

Meilisearch mentions (4)

  • Show HN: Cardstock- Free TCG Proxy Manager for Magic, Yugioh, & Pokemon
    This thing is amazing. Kamal gives me everything I could want (easy console access, easy shell access, a way to manage secrets, a way to see my logs, and letsencrypt support for DNS), all without a PaaS tax. The best part is the accessories feature: https://kamal-deploy.org/docs/commands/accessory/. I am running my main app with two accessories: Meilisearch(https://meilisearch.com) and OpenObserve... - Source: Hacker News / 4 months ago
  • Show HN: Hyvor Blogs – Multi-language blogging platform
    Meilisearch [https://meilisearch.com] for the search index. - Source: Hacker News / almost 2 years ago
  • Meilisearch, the Rust search engine, just raised $5M
    Meilisearch is an open-source, lightning-fast, and hyper-relevant search engine that fits effortlessly into your apps, websites, and workflow. You can find more info on our website https://meilisearch.com. Source: over 3 years ago
  • Search engines for website
    Algolia.com - new plans are very affordable Meilisearch.com - open source. Source: about 4 years ago

What are some alternatives?

When comparing MongoDB and Meilisearch, you can also consider the following products

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

Typesense - Typo tolerant, delightfully simple, open source search 🔍

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

Algolia - Algolia's Search API makes it easy to deliver a great search experience in your apps & websites. Algolia Search provides hosted full-text, numerical, faceted and geolocalized search.

MySQL - The world's most popular open source database

ElasticSearch - Elasticsearch is an open source, distributed, RESTful search engine.

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