To Relational or Not to Relational?

Working on your next project but not sure which back-end technology to use? For starters, databases come in two flavors: relational and non-relational. Both have their own set of rules, pros and cons which help in determining which type of application they should be used in. Let us delve into these differences so that we would be able to decide which one is better suited for us.

Relational Databases:

Relational databases store data in the form of tables containing rows (representing entries) and columns (containing a set of information) having a unique key for each row. These keys can either be primary or foreign. It is based on a form of algebraic set theory known as relational algebra, which is used in the relational modeling of data. They are better suited for applications where many transactions are involved, also known as transactions-oriented applications (OLTP).

They use SQL (Structured Query Language) as a language for the maintenance and querying of databases. We can use MySQL, SQL Server, SQLite, MS Access, Oracle, Sybase, PostGreSQL, or Informix.

They are normalized databases i.e they are in accordance with a series of so-called “normal forms” in order to reduce data redundancy and improve data integrity.

Advantages:

  1. They are useful for applications requiring a lot of transactions, complex queries and routine analysis of data

  2. They are robust, simple, structured and flexible.

  3. They ensure reliable data transactions through ACID (Atomity, Consistency, Isolation, Durability).

  4. Easier to use because of GUI (Graphical User Interface)

Disadvantages:

  1. Their main disadvantage is that it is impossible to horizontally scale them. If our business requirements increase, then we need to move on to bigger systems, making them more costly in the long run.

  2. Images and other multimedia files cannot be stored.

  3. We cannot use them for geospatial data

  4. They can cause ORM Impedance Mismatch

Here_ is a basic CRUD demo of __MySQL _using Node.js. You need to install the relevant software before running the examples in the repository.

#non-relational-database #mysql #relational-databases #nodejs #mongodb

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To Relational or Not to Relational?

To Relational or Not to Relational?

Working on your next project but not sure which back-end technology to use? For starters, databases come in two flavors: relational and non-relational. Both have their own set of rules, pros and cons which help in determining which type of application they should be used in. Let us delve into these differences so that we would be able to decide which one is better suited for us.

Relational Databases:

Relational databases store data in the form of tables containing rows (representing entries) and columns (containing a set of information) having a unique key for each row. These keys can either be primary or foreign. It is based on a form of algebraic set theory known as relational algebra, which is used in the relational modeling of data. They are better suited for applications where many transactions are involved, also known as transactions-oriented applications (OLTP).

They use SQL (Structured Query Language) as a language for the maintenance and querying of databases. We can use MySQL, SQL Server, SQLite, MS Access, Oracle, Sybase, PostGreSQL, or Informix.

They are normalized databases i.e they are in accordance with a series of so-called “normal forms” in order to reduce data redundancy and improve data integrity.

Advantages:

  1. They are useful for applications requiring a lot of transactions, complex queries and routine analysis of data

  2. They are robust, simple, structured and flexible.

  3. They ensure reliable data transactions through ACID (Atomity, Consistency, Isolation, Durability).

  4. Easier to use because of GUI (Graphical User Interface)

Disadvantages:

  1. Their main disadvantage is that it is impossible to horizontally scale them. If our business requirements increase, then we need to move on to bigger systems, making them more costly in the long run.

  2. Images and other multimedia files cannot be stored.

  3. We cannot use them for geospatial data

  4. They can cause ORM Impedance Mismatch

Here_ is a basic CRUD demo of __MySQL _using Node.js. You need to install the relevant software before running the examples in the repository.

#non-relational-database #mysql #relational-databases #nodejs #mongodb

Data Storage in 2021: Choosing the Right Tools for the Job

Reading about the death of the relational database seems like a regular occurrence. However, here we are in 2021, and the relational data store is going strong. If we look at the DB-Engines Ranking website, six of the top 10, including the top four spots, are all relational data stores. Evidently, structured, or relational, data storage is here to stay. Yet four of the top spots are held by non-relational engines. Could that mean that relational data storage is really dying?

The core of this question is not really which kind of data store is better between a relational, normalized structure or a non-relational, denormalized storage mechanism. No, the real core question is: What kind of data store should your organization be using in 2021?

The shortest possible way I can answer this question is as follows:

All of them.

The fact is, you’re much better off not trying to answer your data needs with one, single methodology. Let’s discuss why.

#nosql #sql #data storage #relational database #data consistency #relational data #structured data #non-relational database #data stores #database choice

Ruth  Nabimanya

Ruth Nabimanya

1623224340

Relational vs Non-Relational Databases

If we have a look at available databases, we see a clear line, drawn in the middle. On one side, relational systems like MySQL, PostgreSQL, or SQLite. On the other side, non-relational ones like MongoDB or Neo4j. In this article you will learn the difference between them and which ones, you should use when!

Relational data

Non-relational data

When to use what?

Can I mix multiple databases?

#engineering #database #nosql #coding #sql #relational vs non-relational databases

Easy Explanation Of Relational Deep Reinforcement Learning with Real Code

Due to the memory limitations of LSTMs, most of the current Deep Learning models have used attention mechanisms. A paper titled ‘Deep reinforcement learning with relational inductive biases’ about that topic was already published by DeepMind at ICLR 2019.

Relational environment

In this paper, grid type environment is used to verify the performance of the model. However, it is confirmed that that environment takes too much time to train compared to the quality of it due to the way of moving the block. That is why I decide to use another environment that has relational features but has a simple movement way. After confirming whether the algorithm of the paper works, we can use it in the Starcraft 2 environment.

#reinforcement-learning #relational-intelligence #tensorflow #deep-learning #relational deep reinforcement learning

Brain  Crist

Brain Crist

1600290000

What is a graph database?

Much has been written about graph databases as a distinct type of database in the last few years and it is easy to forgive in believing the accompanying marketing material warranting differentiation of graph databases from any other database.

So what does that marketing material say and how much should you give credit to?

Graph Databases and Graphs

Graph databases are described as databases that operate over graphs and where relationships between things matter. A graph is a type of structure and the underlying graph of a graph database maps the structure, or schema, of the data stored in the database.

The picture below is a graph model for a seat booking database solution for a cinema. We would use such a schema to book seats to watch a film in a particular session at that cinema. I believe it can be readily said that graph schemas are straight forward to look at.

#relational-model #er-diagram #graph-database #relational-databases #property-graph-schema