MongoDB vs MySQL

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MongoDB vs MySQL: What are the differences?

Introduction: In the world of databases, MongoDB and MySQL are popular choices for storing and managing data. Understanding the key differences between MongoDB and MySQL is crucial for individuals and organizations when deciding which database to use for their projects.

  1. Data Model: MongoDB is a document-oriented database, which means it stores data in flexible, JSON-like documents. MySQL, on the other hand, is a relational database management system that stores data in tables with predefined schemas. This fundamental difference in data modeling impacts the way data is structured and queried in each database system.

  2. Scalability: MongoDB is known for its ability to scale horizontally, making it easier to handle large volumes of data by adding more servers to distribute the load. In contrast, MySQL traditionally scales vertically by upgrading hardware resources on a single server. This scalability difference can affect the performance and cost of scaling as the data grows.

  3. Query Language: MongoDB uses a query language that is rich in features and allows for complex queries on nested data structures. MySQL uses SQL (Structured Query Language), which is a standardized language for managing relational databases. The choice of query language can influence the ease of querying and manipulating data based on the application's requirements.

  4. ACID Compliance: MySQL is widely recognized for its support of ACID (Atomicity, Consistency, Isolation, Durability) properties, ensuring data integrity and reliability. MongoDB, on the other hand, sacrifices ACID transactions for higher performance and scalability through its flexibility in data storage. Understanding the trade-off between ACID compliance and performance is essential when selecting the appropriate database system.

  5. Schema Flexibility: In MongoDB, there is no need to define a schema upfront, allowing for dynamic and evolving data structures within the same collection. In contrast, MySQL requires a predefined schema before data can be inserted, enforcing structure and data integrity. The level of schema flexibility can impact the agility and adaptability of the database to changing data requirements over time.

  6. Community and Support: MySQL has been around for a longer period of time and has a larger user base, resulting in extensive community support, documentation, and resources. MongoDB, while rapidly growing in popularity, may have a smaller community compared to MySQL. The availability of community support and resources can play a crucial role in troubleshooting issues, learning, and adopting new features for database systems.

In Summary, understanding the key differences between MongoDB and MySQL, such as data model, scalability, query language, ACID compliance, schema flexibility, and community support, is essential for making an informed decision on selecting the most suitable database system for specific project requirements.

Advice on MongoDB and MySQL
Emre Emrah
Data Scientist/Back End Developer at Hiddenslate · | 5 upvotes · 44.8K views
Needs advice
on
MongoDBMongoDB
and
MySQLMySQL

Hello everyone. We have a project that it's like a candidate tracking system. It has candidates, projects, assessments, etc. A consultant senior developer started it by using MongoDB. The thing is that he designed the database like it's a relational DB.

Personally, I didn't imagine that it was a good thing to do. Because you won't have the power of SQL functionalities like join, on delete, and more. You have to be very careful, I think things may go unmaintainable very fast. I asked him about this and he said "I don't see a problem doing it like this."

What are your thoughts on this? Did you see examples like this? Should I avoid it or go for it? Any advice is appreciated.

Here is what it looks like in Moon Modeler: https://imgur.com/a/RNwNBNY

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Replies (2)
Yoram Kornatzky
Independent Information Technology and Services Professional at DR. YORAM KORNATZKY LTD · | 7 upvotes · 44.4K views
Recommends
on
MySQLMySQL

It happened to me that you actually construct a relational schema with MongoDB. It is not good. You do not use the modeling benefits of MongoDB, and you do not have the benefits of SQL. So I recommend taking it into MySQL. Since you think in a relational way, it is best you move to MySQL

Specifically, do you need non-normalized data? If not, MySQL is best. Otherwise, MongoDB is best. If you think non-relational, you do not need joins, and the problems with cascade disappear.

What is the best way to think? If you work in terms of whole tree of related object, then you think non-relational and non-normalized.

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Praveen Pavithran
CTO at Yatis Telematics · | 3 upvotes · 23.7K views
Recommends

It makes no sense if you use MongoDB primarily as a relational database. As you scale MongoDB will be more expensive than SQL and as you said without having the advantages of "join" etc.

We use MongoDB in our company. It is useful for us, as we work with different types of devices and we love the functionality of being able to add fields whenever we have a new device type etc. Mongo also allows enables easy scaling and fault tolerance. However, you will have to learn how to manage it.

If you are already comfortable with SQL and don't need NoSQL, stick to SQL. At scale, it is cheaper than Mongo.

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Needs advice
on
FirebaseFirebaseMongoDBMongoDB
and
MySQLMySQL

I have been using Firebase with almost all my web projects as well as SwiftUI projects. I use it for the database as well as the user authentication via Google.

Is it good enough?? I have learned MySQL but I'm not that comfortable…

So for user authentication and database should I keep using firebase or switch to MySQL or MongoDB?? Or any other combination?

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Replies (3)
Gulshan Prajapati
Project Manager at Touchmeedia Ads · | 4 upvotes · 50.8K views

Look if you are comfortable with firebase you can go with it, after all, It's all about development and running your program bug-free and fast, but firebase is costly fo long run and if you are comfortable with that cost then I suggest you go with it.

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Jesus Flores
New Technologies Developer at Inteliksa · | 4 upvotes · 65.9K views

Hi!

I’m not an expert, but I can tell you some things:

  • Firebase is a great option for a very simple to implement, fast and reliable authentication method. Nonetheless, the free authentications are limited, so if you will potentially have millions of monthly authentications, it’s probably best to take the time to build it into your app directly.
  • MySQL is great for simple tables where the data structures are not too complex, but it lacks some speed when you are trying to retrieve time data series. Also, I believe it’s a bit more difficult to distribute.
  • MongoDB is great when your information is a bit more complex and you need very peculiar data structures, nested data, dynamic structures, etc. For me at least, it’s a bit more complex to master than MySQL, but the freedom it gives you is incredible. It also performs super fast, especially with time data series, and if I’m not wrong, it’s more scalable.

In general, almost all technologies have their good things, it’s just a matter of what you want to do and then choosing the right ones.

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Recommends
on
FirebaseFirebase

Doing User authentication (oauth) and session management by ourself is kind a challenging, so if possible use firebase itself since it provides these features out of the box.

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Needs advice
on
MongoDBMongoDB
and
MySQLMySQL

I'm starting to work on a Jira-like bug tracker web app. This is a hobby project that is mostly a way for me to learn about different technologies and development processes(CI/CD, etc..) so I could be more ready when I start applying for programming jobs.

I'm debating between MySQL, which I'm less familiar with, and MongoDB which I have used in the past.

My two points of consideration are the following:

1) Which one is more likely to be relevant for web dev jobs? While I want to learn new technologies, I prefer learning ones that will make me more hireable in the future.

2) Which one is more flexible when it comes to changing the shape of the stored data? I expect to need to make some changes as the project goes on.

Thanks, everyone!

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Replies (2)
Recommends
on
MySQLMySQL

MySQL is still more popular than MongoDB if you look at Google Trends. I've also added MariaDB, which is pretty much a copy from MySQL and its features, and PostgreSQL, which is also a popular relational database.

This is a very good article for comparing MySQL to MongoDB and which one you should use: MongoDB vs MySQL: A Comparative Study on Databases.

If you just want to learn and you have the time, I would opt for using both MySQL and MongoDB. For example using MySQL for most of the site content and MongoDB for saving log messages. As you get more and more logs you start to see the benefits from MongoDB's faster document fetching.

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Andy Gee
Freelance Developer at DGTEpro · | 4 upvotes · 70.5K views
Recommends
on
ClickhouseClickhouseInfluxDBInfluxDB

There's really not an awful lot of difference between the two, they have wildly different storage mechanisms but they each have their fairly similar benefits. If you want to learn something that might be a requisite skill for a job, I would also look at alternatives such as time based and column based systems like InfluxDB and the unbelievably fast and flexible ClickHouse. While they may seem like an unlikely fit for a personal bug tracker app, there's no reason not to use them. Since I got into InfluxDB people have been requesting it a lot and I'll be using ClickHouse for all large databases, probably forever. Expand your horizons beyond your competition's.

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Needs advice
on
FaunaFauna
and
MongoDBMongoDB

I’m doing a school project where I have to design a database for a password manager app like 1Password, bitwarden… I’m not sure which database paradigms I should use. Users would have the ability to create vaults and each vault will have many items and can be sorted into favorite, category, tag list… Please help.

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Replies (1)
Amr Saber
Backend Engineer at Aster · | 6 upvotes · 28.7K views
Recommends
on
PostgreSQLPostgreSQL

What I have learned through several years of experience, is that by default you should consider SQL database (like PostgreSQL, MySQL, ...) and if does not suit you then you should explore other noSQL options.

SQL is very solid and it can do almost anything and can support almost any kind of systems.

So, for your case I would recommend that you go with SQL. You should start by listing your use cases and infer from them your entities and relations, and work on them in a Top-to-bottom manner, meaning that you should have some entities that are the core dependencies for the other entities. Or, in other words, they can exist without other entities existing, but the opposite is not true, these are your core entities that you should work on first, then gradually build the other entities.

One way to figure out the core entities is to follow how the users will behave in your system, what will the user create first, and what is dependant on other entities.

For example, in your case, on way to do it is to start with the "vault", as everything else cannot exist without it (and it's the first thing a user would create), then do passwords as they depend on the vaults (I would say passwords are "under" the vault), then once you do them, you can start working on tags then categories, and so on...

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I have a project (in production) that a part of it is generating HTML from JSON object normally we use Microsoft SQL Server only as our main database. but when it comes to this part some team members suggest working with a NoSQL database as we are going to handle JSON data for both retrieval and querying. others replied that will add complexity and we will lose SQL Servers' Unit Of Work which will break the Atomic behavior, and they suggest to continue working with SQL Server since it supports working with JSON. If you have practical experience using JSON with SQL Server, kindly share your feedback.

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Replies (2)
TwoBySea

I agree with the advice you have been given to stick with SQL Server. If you are on the latest SQL Server version you can query inside the JSON field. You should set up a test database with a JSON field and try some queries. Once you understand it and can demonstrate it, show it to the other developers that are suggesting MongoDB. Once they see it working with their own eyes they may drop their position of Mongo over SQL. I would only seriously consider MongoDB if there was no other SQL requirements. I wouldn't do both. I'd be all SQL or all Mongo.

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Kevin Deyne
Principal Software Engineer at Accurate Background · | 2 upvotes · 46.9K views
Recommends

I think the key thing to look for is what kind of queries you're expecting to do on that JSON and how stable that data is going to be. (And if you actually need to store the data as JSON; it's generally pretty inexpensive to generate a JSON object)

MongoDB gets rid of the relational aspect of data in favor of data being very fluid in structure.

So if your JSON is going to vary a lot/is unpredictable/will change over time and you need to run queries efficiently like 'records where the field x exists and its value is higher than 3', that's a great use case for MongoDB.

It's hard to solve this in a standard relational model: Indexing on a single column that has wildly different values is pretty much impossible to do efficiently; and pulling out the data in its own columns is hard because it's hard to predict how many columns you'd have or what their datatypes would be. If this sounds like your predicament, 100% go for MongoDB.

If this is always going to be more or less the same JSON and the fields are going to be predictably the same, then the fact that it's JSON doesn't particularly matter much. Your indexes are going to approach it similar to a long string.

If the queried fields are very predictable, you should probably consider storing the fields as separate columns to have better querying capabilities. Ie if you have {"x":1, "y":2}, {"x":5, "y":6}, {"x":9, "y":0} - just make a table with an x and y column and generate the JSON. The CPU hit is worth it compared to the querying capabilities.

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Needs advice
on
FirebaseFirebaseMongoDBMongoDB
and
MySQLMySQL

Hey everyone, My users love Microsoft Excel, and so do I. I've been making tools for them in the form of workbooks for years, these tools usually have databases included in the spreadsheets or communicate to free APIs around the web, but now I want to distribute these tools in the form of Excel Add-ins for several reasons.

I want these Add-ins to communicate to a personal server to authorize users, read from my databases, and write to them while they're using their Excel environment. I have never built a website, so what would be a good solution for this, considering I'm new to all of these technologies? I know about the existence of Microsoft Azure, Microsoft SharePoint, and Google Sheets, but I don't know how to feel about those.

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Replies (2)

Just definitely don't use firebase. All of MongoDB, MySQL, MariaDB and PostGreSQL have a lot of community support and history.

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Recommends
on
SnowflakeSnowflake

Snowflake is a NoSQL database in the cloud, which also accepts SQL calls. Users can obtain an ODBC driver for SnowFlake, which would allow your Excel apps to write/read from the backend, locally.

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Wassim Ben Jdida
Needs advice
on
GolangGolangMySQLMySQL
and
PostgreSQLPostgreSQL

I am building a fintech startup with a friend, we decided to use Go for its performance and friendly syntax. We want to know if we should use a web framework or just use the pure net/http lib and also for the databases we put PostgreSQL and MySQL on the table, we want to know which one is better, from the community support to the best open-source implementation?

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Replies (3)
Shubham Chadokar
Software Engineer Specialist at Kaleyra · | 7 upvotes · 78.3K views
Recommends
on
GolangGolangPostgreSQLPostgreSQL

Postgres is a better option to consider compared to MySQL. With respect to performance, postgres has an edge over MySQL. Don't use net/http for production. Read this https://medium.com/@nate510/don-t-use-go-s-default-http-client-4804cb19f779 I prefer gorilla/mux as it is simple and provides all the basic features. Other lib seems to be an overhead if you just need basic routing.

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Carlos Iglesias
Recommends

MySQL and Postgre both are great and awesome and great support, community, support. Whatever will be good. Postgree have some little advantages.

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Rafael Breno de Vasconcellos Santos
Recommends
on
ElixirElixir

I recommend Elixir, even though I work in a fintech with Go, Elixir is a FP language so in my opinion the immutability is a important topic when working with money.

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Ilias Mentzelos
Software Engineer at Plum Fintech · | 9 upvotes · 235.3K views
Needs advice
on
CouchbaseCouchbase
and
MongoDBMongoDB

Hey, we want to build a referral campaign mechanism that will probably contain millions of records within the next few years. We want fast read access based on IDs or some indexes, and isolation is crucial as some listeners will try to update the same document at the same time. What's your suggestion between Couchbase and MongoDB? Thanks!

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Replies (2)
Jon Clarke
Enterprise Account Exec at ScyllaDB · | 4 upvotes · 84.5K views
Recommends
on
CouchbaseCouchbaseScyllaDBScyllaDB

I am biased (work for Scylla) but it sounds like a KV/wide column would be better in this use case. Document/schema free/lite DBs data stores are easier to get up and running on but are not as scalable (generally) as NoSQL flavors that require a more rigid data model like ScyllaDB. If your data volumes are going to be 10s of TB and transactions per sec 10s of 1000s (or more), look at Scylla. We have something called lightweight transactions (LWT) that can get you consistency.

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Recommends
on
MongoDBMongoDB

I have found MongoDB highly consistent and highly available. It suits your needs. We usually trade off partion tolerance fot this. Having said that, I am little biased in recommendation as I haven't had much experience with couchbase on production.

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Needs advice
on
MongoDBMongoDBMySQLMySQL
and
PostgreSQLPostgreSQL

I'm planning to build a freelance marketplace website, using tools like Next.js, Firebase Authentication, Node.js, but I need to know which type of database is suitable with performance and powerful features. I'm trying to figure out what the best stack is for this project. If anyone has advice please, I’d love to hear more details. Thanks.

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Replies (3)
Reza Malek
at Meam Software Engineering Group · | 9 upvotes · 180.2K views
Recommends
on
PostgreSQLPostgreSQL

Postgres and MySQL are very similar, but Mongo has differences in terms of storage type and the CAP theorem. For your requirement, I prefer Postgres (or MySQL) over MongoDB. Mongo gives you no schema which is not always good. on the other hand, it is more common in NodeJS community, so you may find more articles about Node-Mongo stuff. I suggest to stay with RDBMS if possible.

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Recommends
on
MySQLMySQLPostgreSQLPostgreSQL

This is a little about experience. Postgresql is fine. You can use either the related table structure or the json table structure.

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Ruslan Rayanov
Recommends
on
MySQLMySQL

We have a ready-made engine for the online exchange and marketplace. To customize it, you only need to know sql. Connecting any database is not a problem. https://falconspace.site/list/solutions

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Dennis Kraaijeveld
Needs advice
on
ExpressJSExpressJSMongoDBMongoDB
and
PostgreSQLPostgreSQL

For learning purposes, I am trying to design a dashboard that displays the total revenue from all connected webshops/marketplaces, displaying incoming orders, total orders, etc.

So I will need to get the data (using Node backend) from the Shopify and marketplace APIs, storing this in the database, and get the data from the back end.

My question is:

What kind of database should I use? Is MongoDB fine for storing this kind of data? Or should I go with a SQL database?

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Replies (3)
Arash JalaliGhalibaf
Software Engineer at Cafe Bazaar · | 10 upvotes · 242.3K views
Recommends
on
PostgreSQLPostgreSQL

Postgres is a solid database with a promising background. In the relational side of database design, I see Postgres as an absolute; Now the arguments and conflicts come in when talking about NoSQL data types. The truth is jsonb in Postgres is efficient and gives a good performance and storage. In a comparison with MongoDB with the same resources (such as RAM and CPU) with better tools and community, I think you should go for Postgres and use jsonb for some of the data. All in all, don't use a NoSQL database just cause you have the data type matching this tech, have both SQL and NoSQL at the same time.

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Recommends
on
MongoDBMongoDB

I have found MongoDB easier to work with. Postgres and SQL in general, in my experience, is harder to work with. While Postgres does provide data consistency, MongoDB provides flexibility. I've found the MongoDB ecosystem to be really great with a good community. I've worked with MongoDB in production and it's been great. I really like the aggregation system and using query operators such as $in, $pull, $push.

While my opinion may be unpopular, I have found MongoDB really great for relational data, using aggregations from a code perspective. In general, data types are also more flexible with MongoDB.

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Luciano Bustos
Senior Software Developer · | 1 upvotes · 232.2K views
Recommends
on
PostgreSQLPostgreSQL

I will use PostgreSQL because you have more powerfull feature for data agregation and views (the raw data from shopify and others could be stored as is) and then use views to produce diff. kind of reports unless you wanna create those aggregations/views in nodejs code. HTH

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Decisions about MongoDB and MySQL
Micha Mailänder
CEO & Co-Founder at Dechea · | 14 upvotes · 81.5K views

Fauna is a serverless database where you store data as JSON. Also, you have build in a HTTP GraphQL interface with a full authentication & authorization layer. That means you can skip your Backend and call it directly from the Frontend. With the power, that you can write data transformation function within Fauna with her own language called FQL, we're getting a blazing fast application.

Also, Fauna takes care about scaling and backups (All data are sharded on three different locations on the globe). That means we can fully focus on writing business logic and don't have to worry anymore about infrastructure.

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As an advanced user, I prefer Postgres over MySQL. MySQL was the first database I learned from my institute. I always have to undergo that infamous date and time dilemma many Java devs know. Both are adequate for a small project. When I worked on a project with a date and time-intensive data, I spent a lot of time dealing with the conversion and transition, leaving me frustrated. I tried Postgres to see how well it can perform. To my surprise, all became a breeze, and the transactions were faster too. I've been using Postgres ever since, and no more dilemma.

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Mike Binks
Founder at BinksDev Software · | 5 upvotes · 45.1K views

The tool I was hosting was a relatively small NodeJS application which utilized the Spotify API - it was meant to be very low maintenance, but still required intervention (to renew certificates, restart the Node app when it crashed, etc). It was also using old NodeJS frameworks that were either deprecated or very outdated.

I made the decision to migrate the service to Google Cloud Run, and change the underlying database from MySQL to RavenDB, for performance and ease-of-use reasons. The move was relatively easy - the only challenge was around migrating from old libraries I was using to perform REST requests, and of course adjusting from a password authentication system to client certificates

I chose to migrate to RavenDB for their advanced dashboard, which allows you to monitor databases, queries, and cluster node performance. Working with RavenDB has been a much smoother and user-friendly experience compared to MySQL.

Hosting the application in Cloud Run, rather than on a dedicated Linux VM, meant that costs were drastically reduced (from £10/month for an AWS EC2 micro instance to £0 for Cloud Run). The serverless architecture means you're only paying when a request is made to the URL - for a small service such as mine, this was a life saver.

Best of all? I get advanced monitoring statistics from Google Cloud, showing me exactly how many requests I get per day, how much memory/CPU is used, and how many container instances are active to serve traffic. When an error occurs, Cloud Trace keeps track of the exception, the line it occurred on, and how many times the error has been seen.

I knew this migration would lead to a low-maintenance solution that I was hoping for, but I didn't realize how low maintenance it would truly be - I haven't needed to even look at the service since it was migrated, aside from checking I allocated enough cores/memory to the containers.

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I’m newbie I was developing a pouchdb and couchdb app cause if the sync. Lots of learning very little code available. I dropped the project cause it consumed my life. Yeats later I’m back into it. I researched other db and came across rethinkdb and mongo for the subscription features. With socketio I should be able to create and similar sync feature. Attempted to use mongo. I attempted to use rethink. Rethink for the win. Super clear l. I had it running in minutes on my local machine and I believe it’s supposed to scale easy. Mongo wasn’t as easy and there free online db is so slow what’s the point. Very easy to find mongo code examples and use rethink code in its place. I wish I went this route years ago. All that corporate google Amazon crap get bent. The reason they have so much power in the world is cause you guys are giving it to them.

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We started using PostgreSQL because there's no need to upgrade to an enterprise plan to access certain essential features. Postgres is essentially plug-and-play; you download it, install it, and there you go!

Another benefit of using Postgres is that you get to use SQL (Structured Query Language)—which isn't for everyone, but I enjoy how flexible and versatile it is.

Postgres also has point-in-time recovery, which you can export wherever you want—This means you can restore data from any given point in time. With this in mind, if you delete something accidentally, you can go back in time and grab said data without restoring the whole database.

Not to mention Postgres is remarkably fast with several thorough benchmarks comparing it to MongoDB, where Postgres mostly came out on top.

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Tjerk W
Founder at Impulz Technologies · | 13 upvotes · 70K views

As a startup, managing my own database, backups and even the schemas/migrations are all overhead. Next to that, I needed both Backend and Frontend ways to write to the database. With firebase this is possible, this saved us some time: Some API calls were not needed because I could directly fetch data in the FE.

Offline support & realtime data updates is also supported out of the box. No need to write your own websockets.

Once the startup grows, moving to a different relational database might make sense. But in a pre-product-market-fit startup, Firebase is a good, and cheaper fit!

The pricing model of firebase firestore is a bit risky. But it saves a lot of time to get quickly to market.

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Asif Khan
Software Development Engineer at Stier Solution Private Limited · | 10 upvotes · 68.3K views

Easy to start, lightweight and open source.

When I started with PHP, MySQL was everywhere so this is how I started with it. I am no expert in databases but I started learning joins, stored procedures, triggers, etc. with MySQL.

Recently used it in one of my projects - Picfam.com with Node.js + Express backend

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We will be getting data in the form of CSVs. Because the data in a CSV is highly structured, it will be easy to create schemas and it works well in a SQL database as opposed to noSQL. For a SQL database, both mySQL and Postgres are very viable options. Both of them are highly performant, definitely enough for our application, even if we needed to scale drastically. Postgres does include some extra features over mySQL such as table inheritance and function overloading. However, the extra features are not advantageous to us given our database use case. Because both databases seemed to suit our use case perfectly, we chose to use mySQL simply because it is more familiar tech within our team.

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One of our biggest technical pillars is to "let the pros manage it", thus we settled on using Heroku PostgreSQL to manage our SQL cluster. We can take advantage of the free tier and the requests will be fast since it is integrated into Heroku. PostgreSQL also support Full text search which can come into handy with manually searching through the tables.

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All the benefits of relational joins and constraints, with JSON field types in Postgres to allow for flexibility like mongo. Objection ORM makes query building seamless and abstracts away a lot of complexity of SQL queries.

MongoDB tends to get slow with scale and requires a lot of code to maintain consistency across collections as foreign keys and other constraints are harder to implement. PostgreSQL also has a vibrant community with battle tested stability and horizontal scalability when needed.

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Pros of MongoDB
Pros of MySQL
  • 827
    Document-oriented storage
  • 593
    No sql
  • 553
    Ease of use
  • 464
    Fast
  • 410
    High performance
  • 257
    Free
  • 218
    Open source
  • 180
    Flexible
  • 145
    Replication & high availability
  • 112
    Easy to maintain
  • 42
    Querying
  • 39
    Easy scalability
  • 38
    Auto-sharding
  • 37
    High availability
  • 31
    Map/reduce
  • 27
    Document database
  • 25
    Easy setup
  • 25
    Full index support
  • 16
    Reliable
  • 15
    Fast in-place updates
  • 14
    Agile programming, flexible, fast
  • 12
    No database migrations
  • 8
    Easy integration with Node.Js
  • 8
    Enterprise
  • 6
    Enterprise Support
  • 5
    Great NoSQL DB
  • 4
    Support for many languages through different drivers
  • 3
    Schemaless
  • 3
    Aggregation Framework
  • 3
    Drivers support is good
  • 2
    Fast
  • 2
    Managed service
  • 2
    Easy to Scale
  • 2
    Awesome
  • 2
    Consistent
  • 1
    Good GUI
  • 1
    Acid Compliant
  • 800
    Sql
  • 679
    Free
  • 562
    Easy
  • 528
    Widely used
  • 489
    Open source
  • 180
    High availability
  • 160
    Cross-platform support
  • 104
    Great community
  • 78
    Secure
  • 75
    Full-text indexing and searching
  • 25
    Fast, open, available
  • 16
    SSL support
  • 15
    Reliable
  • 14
    Robust
  • 8
    Enterprise Version
  • 7
    Easy to set up on all platforms
  • 2
    NoSQL access to JSON data type
  • 1
    Relational database
  • 1
    Easy, light, scalable
  • 1
    Sequel Pro (best SQL GUI)
  • 1
    Replica Support

Sign up to add or upvote prosMake informed product decisions

Cons of MongoDB
Cons of MySQL
  • 6
    Very slowly for connected models that require joins
  • 3
    Not acid compliant
  • 2
    Proprietary query language
  • 16
    Owned by a company with their own agenda
  • 3
    Can't roll back schema changes

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What is MongoDB?

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.

What is MySQL?

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.

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What tools integrate with MongoDB?
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Blog Posts

Dec 22 2021 at 5:41AM

Pinterest

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Dec 8 2020 at 5:50PM

DigitalOcean

GitHubMySQLPostgreSQL+11
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2379
MySQLKafkaApache Spark+6
4
2024
What are some alternatives to MongoDB and MySQL?
Amazon DynamoDB
With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.
Couchbase
Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.
PostgreSQL
PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
Cassandra
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
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).
See all alternatives