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Hello guys.

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So in this section we are going to discuss about the basic differences between RDBMS versus graph database.

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When we talk about RDBMS this is nothing, but this is my relational relational DBMs right database

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management system.

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Along with this we are going to compare with the graph database.

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If I probably take some of the example of RDBMS, it is nothing but like MySQL SQL server, right?

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I hope everybody may have known about this.

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Right.

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And you may have also used it.

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So in order to compare the differences.

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So let me go ahead and write RDBMS over here versus our graph database.

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So the basic difference is that I really want to talk about and this is important before we start,

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you know uh creating our entire nodes properties in graph database okay.

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So first is related to tables right.

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So in r d uh RDBMS uh we basically create tables.

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Right.

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Similarly in graph database here instead of creating tables, we will be creating something called as

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graphs.

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The second important difference is that inside this table we insert records right.

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We insert records.

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And this records will be something called as rows right.

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In the case of graph database we specifically use something called as properties and its it's values.

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Right?

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So here, instead of saying it as zeros we specifically say it as properties.

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The third thing over here and again we will be discussing about all these things when we do it in our

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practical implementation.

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If I probably talk about tables rows are there.

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Rows are for rows records right.

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Whenever we insert a record.

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But in every row there will be some kind of columns.

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And with respect to this columns, there will be data also.

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Right?

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Some data will definitely be there.

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So similarly over here, uh, sorry.

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Uh, this rows uh, I just need to make some change over here.

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When we say rows right over here inside this graph database we have something called as nodes.

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Okay.

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Nodes.

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Now this nodes will be like this circular structure.

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Right?

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It can be an entity.

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It can be a name.

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Something like that.

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When we talk about columns and data these are nothing.

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But it is basically properties and values.

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Properties and values.

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So how we represent columns and data in RDBMS.

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Similarly in graph database we represent it as properties and values.

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Then uh coming to the fourth and the important point which is called as constraints.

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I hope you have heard about this kind of constraints, where you have something like primary key, where

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you have foreign key where you have candidate key, right?

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So different types of keys are there.

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And the reason of making keys is that there will be a dependency of another table in a specific table

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itself.

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Right.

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Similarly, over here we if we really want to create constraints in graph database, we basically create

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relationships.

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Relationships like one of the example I told.

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Right.

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So this is my two nodes.

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And this may be related to this right.

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Let's say over here I have Tesla.

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This is a company which is owned by Elon Musk.

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Right.

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So I can just go ahead and write owned.

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Right.

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So owned is basically a relationship.

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And in tables, uh, most of the queries we write a lot of joins, queries itself.

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Right now instead of writing join queries in graph database we specifically use something called as

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traversal.

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Traversal basically means based on the properties based on the nodes, based on the relationship, we

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travel from one node to the other node to finally get a result right.

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So these are some of the basic differences between RDBMS and graph database, right?

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Instead of using tables, we use graph over here.

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Instead of inserting records or rows, we create nodes over here.

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Then we have columns and data.

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Instead of columns and data we use properties and values Similarly, with respect to constraint we have

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this primary key foreign key candidate key in RDBMS.

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Similarly here we have relationship and instead of join queries we use something called as traversal.

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Now let's talk about some of the important advantages.

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So let's go ahead and talk about advantages of neo4j's okay.

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Now there's some very good advantages.

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First, entire this neo four J database works with respect to a graph data model.

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We will talk more about this graph data model.

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Uh, this graph data model will be responsible in creating this nodes um relationship properties and

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values and many more things properties and values.

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Okay, now coming to the second and very important point, when we use this neo for Jay in the cloud,

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it provides us real time insights, like as soon as I create a graph, because see, at the end of the

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day when we use this neo 4G there, you could see in that particular instance nodes were getting maintained

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in a separate way.

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Properties were getting maintained in a separate way.

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The relationships were getting maintained in a separate way right here.

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Uh, you'll be able to see that if I go to the third point, you will be able to retrieve the data very

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much easily just by writing one query.

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And over here we will be learning about this, which is called as Cypher query.

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like how we have a sequel query.

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Similarly, we'll go ahead and uh, write the cipher query.

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And sometime you don't even have to write the cipher query, right.

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Just by clicking on any of the relationships.

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And all automatically will be getting a basic template of all the queries itself.

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And that is all possible because of this Neo4j's database.

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Okay.

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As I said, uh, let's talk about this Cypher query.

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So we basically say Cypher query as this Cypher query language.

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Cypher query language.

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Right now inside the Cypher query language.

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Uh, it is you can just say it as it is a declarative.

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It is a decorated declarative query language.

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To represent.

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The graph.

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Visually.

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It is used to represent the graph visually.

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Okay.

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And the best thing about Cypher query will be that you'll be able to understand in a very much easy

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way, because it is human readable.

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Okay.

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And one of the very important thing that usually in RDBMS you sometime when there is a nested queries

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and all, you really have to use lot of joints.

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But uh, in neo4j's you don't have to use any joints.

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That is the best thing.

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So that makes this entire Cypher query language amazing for doing multi different different purposes

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for retrieving different, different kind of data itself.

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Okay.

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Uh, so we will be talking more about it as we go ahead.

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And I've also spoken about the advantages of neo for Jay, but if I probably talk about most of the

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common properties like acid properties, it supposed, uh, it neo four J supports complete acid properties,

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right?

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When we say acid, what does this basically mean?

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In RDBMS there are four important properties.

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One is atomicity, consistency, isolation, and durability.

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Right.

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So let me just go ahead and write this.

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It is nothing but atomicity.

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Okay.

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Consistency.

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Isolation.

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Along with this you also have this durability.

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So with respect to this acid properties which is one of the core features of RDBMS.

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Similarly this is also supported in Neo4j's.

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Um and um, you'll be able to see that, uh, once you start using this, there is no such kind of fixed

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schema.

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Okay.

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So one of the very good advantages with respect to Neo4j's is that we don't have any fixed schema.

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It is having a flexible schema okay.

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It's not like that one of the node will have only three properties.

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The other node will also have three properties.

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No, nothing like that.

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It can have any number of properties.

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It can depend right based on the data that we have.

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So this was just to give you a clear idea about the differences between RDBMS and graph database.

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Along with this, we also saw what are the advantages of uh specifically using neo for J.

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Okay, now, uh, in the next video or in the next section, we are going to discuss about the data

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model in Neo Forge.

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And that will actually give us a crux, understanding about how a nodes is basically created.

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What are the important things?

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What are the important components.

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When we go ahead and create this kind of nodes?

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By using Neo Forge database, by using the Cypher query language, I this was it.

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I will see you all in the next section.