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I'm currently developing an app that ranks trending stuff ( such as games, memes or movies, etc. ) or events in a particular country or region. Here are the specs: My app does not require registration and requires cookies and localStorage to track users. Users can add new entries to each trending category provided that their country of origin is recorded in cookies. If each category contains more than 100 items then the oldest items get deleted. The question is: what kind of database should I use for managing this app? Thanks in advance

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I think your best and cheapest choice is going to be MongoDB, Although Postgres is probably going to be the more scaleable approach, you likely have a good idea of how you want to present your data, and the app seems small enough that you shouldn't need to worry about scaling issues. It also sounds like your app can grow in a linear capacity based on the number of users, and the amount of data, which is the perfect use-case for noSQL databases (linear, predictable scaling).

Correct me if I have any of these assumptions wrong. 1. You're looking to have a relatively high-read with a lower write volume 2. Your app is essentially a list of objects that can belong to a category 3. users can create objects in this list.

I think Mongo is going to be what you're looking for on the following basis: 1. you absolutely need a database that is shared by all users of your app, therefor IndexedDB is out of the question. 2. You have semi-structured data 3. you probably want the cheapest solution.

I think Postgres is wrong for the following reasons: 1. your app is pretty simple in concept, SQL databases will add unnecessary complexity to your system, either through ORMs or SQL queries. (use an ORM if you go with SQL) 2. Hosting SQL databases for production is not cheap! the cheapest solution I know of for Postgres is ElephantSQL. It provides 20MB for free with 5 concurrent connections, you should be okay to manage these limitations if you decide to go Postgres in the end. Whereas mongoDB Atlas has some great free-tier options.

Although your data might be easier to model in Postgres, you can certainly model your data as a single list of items that have a category attached.

I don't want to officially recommend another tool, but you should really checkout prisma, firebase, amplify, or Azure App Services for this app! Just go completely backend-less [Firebase] [Amplify] [Prisma] [Azure App Services]

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Pros of IndexedDB
Pros of Redis
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    • 881
    • 538
      Super fast
    • 510
      Ease of use
    • 441
      In-memory cache
    • 321
      Advanced key-value cache
    • 190
      Open source
    • 179
      Easy to deploy
    • 163
    • 152
    • 120
    • 40
    • 39
      High Availability
    • 34
      Data Structures
    • 32
      Very Scalable
    • 23
    • 20
    • 20
      Great community
    • 17
      "NoSQL" key-value data store
    • 14
    • 12
    • 10
      Sorted Sets
    • 9
    • 8
      BSD licensed
    • 8
    • 7
      Integrates super easy with Sidekiq for Rails background
    • 7
      Async replication
    • 7
    • 6
      Keys with a limited time-to-live
    • 6
      Open Source
    • 5
    • 5
      Lua scripting
    • 4
    • 4
      Awesomeness for Free!
    • 3
    • 3
      Runs server side LUA
    • 3
      outstanding performance
    • 3
    • 3
      LRU eviction of keys
    • 3
      Written in ANSI C
    • 3
      Feature Rich
    • 2
      Performance & ease of use
    • 2
      Data structure server
    • 1
    • 1
      Channels concept
    • 1
    • 1
      Temporarily kept on disk
    • 1
      Dont save data if no subscribers are found
    • 1
      Automatic failover
    • 1
      Easy to use
    • 1
      Existing Laravel Integration
    • 1
      Object [key/value] size each 500 MB

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    Cons of IndexedDB
    Cons of Redis
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      • 14
        Cannot query objects directly
      • 2
        No secondary indexes for non-numeric data types
      • 1
        No WAL

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      What is IndexedDB?

      This API uses indexes to enable high-performance searches of this data. While Web Storage is useful for storing smaller amounts of data, it is less useful for storing larger amounts of structured data.

      What is Redis?

      Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

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      Nov 20 2019 at 3:38AM


      Jun 6 2019 at 5:11PM


      What are some alternatives to IndexedDB and Redis?
      SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.
      PouchDB enables applications to store data locally while offline, then synchronize it with CouchDB and compatible servers when the application is back online, keeping the user's data in sync no matter where they next login.
      MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
      Apache CouchDB is a database that uses JSON for documents, JavaScript for MapReduce indexes, and regular HTTP for its API. CouchDB is a database that completely embraces the web. Store your data with JSON documents. Access your documents and query your indexes with your web browser, via HTTP. Index, combine, and transform your documents with JavaScript.
      The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
      See all alternatives