SQL vs NoSQL or MySQL vs MongoDB 

0:36 SQL 9:00 NoSQL 13:13 Differences

I dont think I will ever be grateful enough for Maximilian. This man single-handedly taught me everything from HTML, CSS and basic JavaScript, all the way to Vue and React, Node.js, databases and REST API. Thanks to you I got a highly paying job, and can make anything that comes to my mind. Thank you sir from the bottom of my heart. :)

A key concept in this comparative analysis is consistency of information. - SQL (Relational Databases): a good design (scheme and constraints defined correctly and transactions are used properly) allows the database engine to guarantee consistency based on that design. - NoSQL: lower consistency of information (it is a responsibility of the developer to ensure consistency... some time this could be very difficult).

God bless this "vs" videos they are so good.

Man you knowledge base is beyond human scope...really. When i first started learning programming there where many times i coulnd't get you, after learning programming there a lot of times i realize how many miles ahead you are. RESPECT.

Thank you for this! I've been tasked to build a DB, but wasn't sure which type to go with. I tried using MongoDB and I can see where it has it's advantages. After watching this though, an SQL DB is better for our needs.

Hi, thank you for putting the effort and time to explain in such understandable way the differences between SQL and NoSQL. I appreciate your effort ! Good Luck!

Tremendous explanation. I have spent 3 days reading tons of information about differences between SQL and NoSQL, and have understood less than I expected, but this video made everything straightforward. Thanks to the author! Great work!

Horizontally scaling SQL isn't very difficult but it requires a backend to do some extra work behind the scenes (which isn't terribly hard to program). Implemented properly and under certain conditions it can be slightly faster than NoSQL. You can use Schemas with NoSQL, see tools like Mongoose. Mongoose also makes relations very easy with the populate function. If the data isn't likely to change frequently it would still be better to just nest the data you need and update it as needed for speed though. So SQL horizontal scaling: possible but more difficult than NoSQL. NoSQL: Schema-optional with reverse-compatible changes via some well documented apis Aside from those excellent video

This is hands down the most concise and relatable explanation of a SQL-like database vs a NoSQL-like database I have ever seen. Random tips: -A good intro to SQL is reading Chapter 2 of the official PostgreSql manual. -As a frontend dev, it's easier to "pick up" NoSQL. Since NoSQL is literally a folder of JSON files that you can search(query) through. -But, it's easy to dig yourself into a hole if you duplicate your data in several locations and then need to update that same piece of data. -You can also hurt yourself when your not consistent with your property names. For example "first name" can be found as "f_name" or "firstName" in your NoSQL database -Just be careful, and very consistent when using NoSQL. For total beginners, I recommend to go with SQL and then migrate to NoSQL if needed. Think of SQL-databases as a really powerful sportbike motorcycle with really good training wheels. It's safe and you probably won't outride the bike.

Thank you for the great explanation! I've been looking up a lot of information about databases and this is by far the best and most helpful video!

There are special commands so called "choins" @8:31 :-) I really love this german accent! Thank you for this comparison, very interesting and complete.

Another important thing to consider for SQL databases is the amount of time conceptualizing a SQL database takes. For an effective SQL db you need a proper ERR Diagram and schema that takes into consideration a ton of user interactions. One wrong step at the conceptualization phase and your whole relational system breaks. Similarly, the modification anomalies that may come from NoSQL can break your db, but to a more manageable extent IMO. When agile development reigns king, quick development with short conceptualizing phases means your better off with NoSQL despite the downside to writing-heavy applications. What do you all think?

This is the most clear explanation of SQL and NoSQL on RU-vid.

Horizontal scaling (also called _scaling-out_ ) is challenging and can be inherently inefficient with a _shared-nothing_ SQL database like MySQL, as mentioned in the video. However, there *are* indeed _shared-storage_ SQL databases that are designed to dynamically scale-out (horizontal scale) seamlessly. This is accomplished by replicating the database _structure_ on each server node, but with virtual programmatic pointers in each table, rather than the actual rows (records) of data themselves. These pointers point to corresponding table structures on distributed Storage Area Networks (SANs) that contain the actual rows of table data. Given this complexity, an enterprise-grade dynamically scalable shared-storage SQL database solution like Oracle 18c is very expensive to acquire, implement, administer and support. During the mid-2000s, Larry Ellison used to love to brag about the horizontal scaling capability of Oracle's shared-storage SQL offerings verses IBM's DB2 shared-nothing SQL database.

Great video. One of the other key things SQL databases tend to have over NoSQ databases are transactions. i.e. ACID (Atomicity, Consistency, Isolation, Durability) support. But, there is an argument that, if you structure your NoSQL documents well, ACID is not needed

Brilliant explanation! I have a feeling that I can learn anything by watching your courses!

I really like this video with one singular exception. When discussing relational databases at 1:48 minutes into this video the narrator says: "The database we typically use is a relational database that means we have a database which works with certain assumptions". No other mention or explanation is given for this. Also there is never a mention of NoSQL databases working "with certain assumptions". I've designed/modeled and built relational databases for 19 years. I base every relational database design on one thing: Rigorous due diligence in requirements discovery and analysis. This means: 1) Requirements 2) All the requirements 3) Nothing but the requirements The one thing I NEVER base my relational designs on is "assumptions". No good relational database design should ever be based on assumptions.

Thanks for a great general comparison... I know this is old, but thought I'd mention one thing that I think is overlooked in this video although technically correct. Specifically regarding relations and schema consistency. While you are correct in saying that it is not directly supported in Mongo, this responsibility is instead handed over to the ORM layer. Typically, at least in Rails with Active Record, you add all the schema enforcements and relational requirements in that layer instead. By doing that you eliminate most of the downsides you mention regarding data consistency. One other key feature that I think should be mentioned too is that you can create much more advanced data structures in the documents themselves. This is a very simple example, but lets say you wanted to quickly wanted to know which users ordered a specific product. One way to solve that would be to have an array of user_ids on the product collection which essentially acts as a has_many relationship. When displaying products you could easily describe how many users bought this product and even show if friends of the user bought the product (provided you have a collection for that data too). Maybe a stupid example, but hopefully you get the idea. I would say that the biggest downside to using mongo is if you have a lot of requirements to run group by queries. Although it is possible in mongo with aggregations, it is not as straight forward. For me, unless I'm writing a banking application, I would select mongo for every web application I would build. :)

You have explained it very nicely Max. Cheers!

Will this video get a sequel?😂

Your ability to teach, explain things is absolutly awesome. Im watching a lot of diffrent famous IT youtubers but your content is gold and definitly the best. You probably created more IT devs than any university of the world ;)

In terms of RDBMS a "relation" actually means a table (because it stores rows of "related data" - that is structured records vs just a bunch of values). What he calls "relations" are properly called "foreign key constraints".

Definitely needed this! I've hear NoSQL was faster than SQL, so it seemed very attractive. But most of my projects rely on the integrity of the data shared across different Models. This video has persuaded me to stick with SQL lol. The fact that updating one NoSQL Collection has no affect on linked Collections is a big downside. Thanks 👌👌

It's actually not about SQL vs NoSQL but relational vs non-relational. SQL databases come with a lot of constraint and behaviors (triggers) and if your data is highly relational, you will have an advantage using SQL databases maintaining your data structural integrity. On the other hand NoSQL databases are very restricted in relational integrity enforcement tools, but they are faster, easier to operate and learn and are very convenient for specific tasks. In general, use relational database if you're not sure which type of DB to go with. It might require some extra planning but won't lead you to data integrity issues and migration to NonSQL will be mush easier. At the point you face the need of sharding you will surely be well aware of what type of DB you need and how to shard your data well. So I'd not worry about scaling at this point.

I have used both SQL and NoSQL databases for decades and favored NoSQL until about 10 years ago when I discovered the incredible power of data analysis using SQL. I found that hundreds of lines of complex Python code manipulating data tables could be reduced into a few simple lines of SQL joins and aggregations.

Wow, this is a great information. As a beginning SQL learner, I got a good chunk of knowledge from your video. Thank you!

Thank you soooooooooooooooo much. Finally understand, it's not necessary to use MySql with PHP & MongoDB with NodeJS. Both the database has difference perspective depending on the scaling, reading/ writing, updating & relation factors.

Good thing I found this video, and from a web developer/full stack RU-vidr. Needed to see which sql to choose to learn.

19:00 summary is pretty solid.

13:00 you can save the user id in the user field of the orders collection, and when you query the orders collection, you populate the user field. this way the data does not get duplicated, it works just like a relation

We use an SQL database at work specifically PostgreSQL. Our "rules" for our schema all tables need a primary key as a sequence that is either called seq or id. If that tables p_key is not referenced in another table we call it seq if another table does use it, its called id so a user table would have a column id, then on the table referencing there would be a sequence and a column called user_id. All of out many to many tables we call tablename_xref (xref for cross-reference) so just looking at the database it makes a ton of sense. we also add control columns on every table prefixed with ctl we have an insert user, insert time, update user, update time the times are stored as dttm (time with timezone). any anytime a user inserts data or updates data its reflected in the control columns.

This is the best introduction to the difference between SQL v.s. NoSQL databases on RU-vid. No wonder why this video gets near 2M views.

I tried to get into NoSQL and every time I did I basically ended up creating a system and imposing schemas and basically just making it a somewhat messy SQL style db.

Really thanks for sharing, now I finally understand the difference. Some hints: horizontal scaling for SQL is possible (at least for MySQL and Oracle), of course it's trickier than the vertical scaling. The use of the same colors for SQL/NoSQL and Horizontal/Vertical Scaling is a bit confusing.

Great video 👍 Could you maybe have a part 2 of this that provide practical examples, eg. Pointing out a few tech companies that are using different type of DBMS and how do they store or work with their current data. For a fresh graduate like me that do not have industry experience, it will give some insights when searching for job roles

and talking the presentation of data and visualizing it (for us, developers), both nosql and sql data can be represented as tables with columns and rows, this makes it simpler for the eyes to see and read.

"Which database is better? Which one should you use? " PostgreSQL. That has a JSONB type whic means you can store Json documents and query them, and it has all the required features of a database: transactions, replication etc. Plus it has a large number of free extensions that enable you to connect it to mysql or oracle or even an XML or CSV file as a data source. PostgreSQL exlipses the abilities of MySQL, really, and it's also free.

It really does depend on your line of work as to which type of database to use. In my line of work, 95% of the time you would use a no-SQL type such as Elasticsearch. But, as he mentioned, something like an order database, you would be better off using either SQL or an hybrid approach.

Relations = Tables (Product Table) Relationship = Relationship (One to One) Relation != Relationship that's the db language as we learnt it from our teachers

Thank you , To make it short : if you want more data customization use sql , and if you will do an archive-ish data (read and write a lot with rare update )use no sql

It means "not only sql" (= noSql,) but not NO sql at all

Your video let people easily understand this kind of stuff that is not easy at all. My compliment for the clarity of your communication, well-done video! If you allow me, I just don't "agree" about the word "impossible" in horizontal scaling an RDMS. Modern relational DB can have good, fast and efficient horizontal scaling as well (Multitenant with shards, connection routing based and read/write routing base for example) when used with some cluster manager like Galera or MaxScale. I agree that is not an easy implementation and can have some deadly pitfalls such as high costs, set up complexity, weak schema design.

Great video. I would add that with federated tables, json queries and so on, SQL is quite capable of doing everything you mentioned in a noSQL setup, but the cost is overhead. Ive never seen an instance where I couldn't horizontally scale an SQL database. Can you provide any examples of this?

Great video! Thanks for it. I would change the colors on the slide about horizontal/vertical scaling though. They are the same as when comparing SQL and NoSQL, and could lead to confusion, letting people assume Horizontal Scaling = SQL and Vertical Scaling = NoSQL

Thanks for this video Max!! Comparison slide was more helpful.

I have watched a BUNCH of videos on this subject and this was the best one by far. THANK YOU!

Good video, but sounds like you are a pro NoSQL. However the disadvantages of SQL stated are not entirely true as scalable distributed framework becomes more developed. With the structure and reliability of MySQL and the high scalability of Hadoop and performance improvement offered by both worlds, what you get is a powerful Relational, very reliable, less messy database. NoSQL is great but I just hope the looseness doesn't over complicate an already complicated ecosystem. Some of the relatively poor designs of the Internet is still causing a lot of problem currently. Overall "All Models are wrong, but some are useful"

I've watched a handful of videos explaining this and this was by far the best, great video.

thank you man!!! You are the best in this theme!

This is one of the few "VS" questions that really is useful, it comes up all the time in job interviews.

I like most of the description here since I was trying to better understand the NoSQL standpoint. However, I do want to point out that not all SQL implementations are limited on horizontal scaling. Oracle DB since 10g (and better since 11g) has the ability to RAC scale horizontally and keep the data synched between nodes (servers). You do have to properly design the data distribution for such a setup, but when properly designed there is little to no limitations on scale.

A very important difference that is not mentioned in this video is transaction.

Just amazing, the way you described both of those database system, really saved me a tons of time surfing through out the internet and reading tons of materials. Thank you so much.

And one more comment about scaling. Horizontal scaling is possible in SQL world. Many servers offers 'replication', MS SQL Server offers also linked servers and so on. MySQL offers Clusters. So saying that in sql world only vertical scaling is possible is not 100% correct. Performance of the queries can be improved by indexes but also sql servers optimizes queries to be the most efficient. Also mysql offers few engines, eg. myisam with very limited functionality but very fast, and innodb which can be very strict and safe, but reduces performance. Additional question is which kind of database will require more hardware resources sooner, sql keeping just one entity of the data, or nosql storing same data multiple times ? ;)

Great! This content helped me a lot to decide wich db I have to learn now. Thank you bro, hugs from Brazil

just was wondering about this topic and bam!!! the notification, sql vs nosql.. .. thanx max

My school paper just got a bit smarter because of you. Thanks!

Well people, just don't be confused with this incorrect description of SQL horizontal scaling possibilities, it explained here completely wrong. SQL scaling very good and not hard at all last several years, just use correct DB for your purpose.

Thanks for sharing a very elaborated comparison of SQL vs NoSQL. At 19:46 of the video you mention we can face issues if DB becomes really really big. I have a some questions here: 1- What are the issues and which DBMS is favored? 2- Can you give an idea in terms of Gigabytes or number of records where we start thinking its becoming really really big? 3- Which one is easier for writing code for CRUD ops ?

Thank you! Helped me alot! I was struggling to decide which one I would use in my project because I don't knew these core differences and concepts. (I really enjoy and understand most of what you teach and that's the reason why I bought some of your courses, even that english it's not my first language)

Excellent video for people planning to move from SQL to No-SQL world. Concise and to-the-point comparison.

Thank you very much Max for explaining deep topics in simple and easy way

SELECT location FROM places WHERE name = Waldo Joking aside, here's a summary from a retail perspective: SQL: user/supply tables that are fluid. NOSQL: order/purchase data that are concrete history Your app pulls up the purchaser/supplier from SQL (change in addy, change of name, change in credit), and then the complete exchange history from NOSQL.

Off topic: I did the Complete React Course from this amazing dude and its great!

Just an amazing explanation! Thank you for such a wide and comprehensive comparison.

I struggled to learn database until this tutorial. Thanks alot.

That is impressive and very clear explained. Even I am not native English speaker, I have understood everything. Would like to see more from you

amazing. I finally understand now.

I will remind you that a SQL database is a term, not just a language. A SQL database is a database engine created to perform queries from tables. Today we have: 1) Tables only. These tables can me hooked up from different engines. 2) Tables + the engine The engine itself must be ready for relational bindings between tables, and ready to perform queries from all the tables.

how about comparison in terms of clarity, reliability, maintainability of code for the two types of db? (my gut says the flexibility of nosql implies more sophisticated/complex code implies reduced clarity, greater likelihood of bugs, etc .. but .. my gut is not a reliable source of info.)

2 years later from this video update and its super nice to hear all this information!

Now do Graph databases like Neo4j or Multi-model databases like ArangoDB

I like the nosql example for orders. It shows how nosql can easily retain historical data. When a product is changed, then a customer who ordered in the past, didn't actually buy the updated product. The order still shows the product how it was at the time of ordering.

Appreciate the breakdown!

Quite clear and smooth explanations. Much appreciated. Looking into taking your MongoDB course in the near future.

like your clear pronunciation

Good explanation. It's worth mentioning that retrieving the price of products within an order by a relation is not desirable - the product price can change, while the price in the of an existing order line item should not

wow, this was an amazing tutorial. Thank you very much sir!

schema-less is best here, if the field is not there it is the same as null in the other world, but without a schema the database is easy to update when you get a new version of you program

For complicated ERD, use SQL, For a simple database, use NoSQL (Firebase, MongoDB, etc..)

You can sure use NoSQL for storing different kinds of data and use structured links to that data with using SQL. Or you can just add a text field to store json format inside the SQL database to make it act like NoSQL. I'd suggest using SQL with Text fields to store jason format data with many multiple and each different sub fields to access. It is just easier and you won't need two database installations taxing your hardware.

I can tell you as a data analyst not organizing your data should be a punishable crime. Websites gather lots of data which is important to the business it is supporting. Without proper organization there is no practical way to use the information in any databases you create as reliable business tools. I work very hard every day just gathering haphazardly stored data into hopefully meaningful reporting with mixed results. Please whatever data storage technology you choose please consider how that data can be retrieved and used to inform the underlying business. This should not be an afterthought but it almost always is.

I am working my way through your Udemy course for MongoDB and it is amazing and I am learning a lot and really enjoying it

Maybe I'm wrong but I think few things needs to be clarified, or at least discussed ;) 1. In SQL world 'relation' it's a synonym of 'table', connection between tables is called 'relationship', so all 'relations' from the video are 'relationships'. 2. Typical sql server like mysql, mariadb or so does not allow many-to-many relationships; That one shown in 5:09 is not many-to-many, there are two relationships one-to-many. Some languages, eg. C# or Java, allows to manage many-to-many relationships, but there are not done on sql server side.

that is simple: you write in sql then create an api that load from sql then write in Nosql and finally only read from nosql

You convinced me: I'm going to stick to SQL.

Really, really, good, clear description!!! Thank you so much!

Didn't expect to get this with one video. You did it man. Keep going ✌️

Thank you so much!) Great explanation))

This video is great. I like it. I 'm using mysql for 5 years now and when I heard for the first time about nosql, I didn't actually understand the way it wa structured, today I found out with this very video. thanks

School or no school?

It's so unfair dislike/thumb-down this resourceful video. Its 2020 and its so valid..Thank you.

Hey! I recognize your voice from my React Udemy course! Great job, sir! I highly recommend his courses on Udemy!

This video explains the basic difference, there are few points I want to add: 1. NoSQL is more intuitive in real life. Think about a patient filling up a form in a clinic. SQL needs to break the data down into few tables, set all the columns and check all the types to process it. but NOSQL just save the whole document into the collection. It can be a complicated structure with array and nested obj in the document. This is the idea of row based vs document based. I found that I have saved lots of time of dealing with the database structure in SQL. That makes my development more effective. But of course, you need to know what you are doing or you will mess it up. 2. A major factor of choosing is what language you use in your service layer. If you use Node.JS (this is the most famouse one now), very high chance you will choose NoSQL becuase it just work so great together. The data you store and the object you process in Node is exactly the same (JSON)! This just save lots of conversion and mapping work. 3. Most of the people using MongoDB will define a schema on top of it, so that schema-less selling points just go away. But it is still a lot easier to modify the schema. You don't need ALTER statement to alter the table. That's save lots of hassle in deploying a new version. 4. The more experience I get with NoSQL, the more I realise how much it can replace SQL. It looks messy and you won't feel good in the beginning. But it's just the other way of organizing your data. You will have less relationship, and your relation join will be happening in the service layer. But if you are doing highly transaction application (Like a bank or payment stuff), you should still use SQL. The way you can open transaction, commit it, or roll back. You can never do this so well in NOSQL because of it's nature of lacking relationships across documents and collections.

If it were me, I would use the nosql approach but create my own relational structure. With various operations, you would either display some information or store some information. The function called for either purpose would be specifically curtailed to do the task efficiently, even across multiple collections. With this approach you get the speed and flexibility of a json based database, but you also get the regimentation necessary for succinct correlation. An alternative is the use of json strings within a SQL db. No reason whatsoever you ant store a json collection in a field within MySQL for instance.

Database course plz

Thanks for the quick overview... I really needed that!

Thank you! Just what I was searching for 🤸

Years ago I took a course of ObjectStore, it's like NoSQL where you store objects like in memory but in a object database.