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  Asynchronous Communication (Non Blocking Call) 1. Time Delay 2. Work from home 3. Youtube video's comment section 4.When computation takes long time; Flipkart page open but processing takes time 5. Scalability of application ; It doesn't wait for notification from another user placing order 6. Avoid Cascading failure ; At times if with response server becomes overload ,it is made asynchronous inorder to let server work on it. 

  Synchronous Communication (Blocking Call) => Handshake 1. Real Time 2. 1 to 1 communication 3. In person / zoom meeting 4. Quick Reply to question

  Normalization: Putting data in multiple tables to avoid redundancy. It combines data & organises it in a single table.

  Polyglot Persistence: Application requires multiples types of database Here multiple types of DB is used to perform operation in application. ***if you store data in disk, it will persist even if database server goes down. ***if you write data in memory, it will not persist as database server goes down.

 Google Maps: Graph DB Linkedln: : GraphDB E-commerce Cart : Key Value DB Machine Learning : Columnar DB

  NoSQL Database: It stands for "non-SQL" database / non-relational database. NoSQL is the umbrella term comprising of four different types of DB. Key Value DB Generally used for caching Example: Redis   Document DB Bring best of RDBMS & NoSQL It comprises of relational concept for RDBMS & dynamic schemas and horizontal scaling from NoSQL databases. Example: MongoDB   Columnar DB Columns are stored together instead of rows. It is used mainly in data analysis. Example: Cassandra   Graph DB It represent & stores entities in form of graph data structure. It is mainly used for social network. Example: neo4j

 RDBMS  Software That performs data operation on relational database Operations Store, manage, query & retrieve data Tables Data is stored in the form of tables Foreign Key Relation between two tables is represented by foreign keys Advantages : No data redundancy & inconsistency Different User refer to same table, avoid inconsistency Data Concurrency A locking system is provided by RDBMS to prevent abnormalities from occurring **Until 1 st transaction get over, 2 nd transaction is not performed   Data Searching Built in searching capabilities **Using queries you can search Data Integrity Constraint restricting allow it to follow according to rules Problem : 1. Rigid Schema : We cannot add new column in a table 2. High Cost : 3. Scalability Issues : Horizontal Scaling / Sharding is very difficult.

  File Based Storage System  A file based storage system is a database management system where data is store in form of files. Challenges: 1. Data Redundancy - Update/ Delete Anomaly leads to data inconsistency. 2. Poor Security - Some data is present in the system which causes possibility of data breaches by                                              unauthorized users. 3. Slow - Speed is slow . Due to which data retrieval is not very efficient.

  Round Robin - Rotation fashion Weighted Round Robin - It is similar to round robin when server are of different capacities. IP Hash Algorithm - The server have almost equal capacity & hash function(Input is source IP). It is used for random  or unbiased distribution of requests to the nodes. Source IP Hash - It combines the server & client's source & destination's IP addresses to produce hash key. Least connection algorithm - Clients requests are distributed to application server with least number of active connections at time client request is received. Least response time - Request is distributed based on server which has least response time.

Load Balancing It is the process of efficient distribution of network traffic across all nodes in a distributed system. Role of Load Balancer 1. The Load distribution is equal over every node. 2. Health Check ( if node is not operational ,request is passed to that node that is up & running) 3. Load Balancer ensure high scalability, high throughput & high availability 

  Replication = Redundancy + Synchronization It involves redundancy , but involves copying of data from 1 node to another or synchronization of states between nodes. Active Redundancy Data in all the  server are same & in synchronization. Passive Redundancy Every Read-Write => Done By Master If master goes down ,then one of the slave becomes master Master-Slave Replication can be either synchronous/ asynchronous  Difference is simply timing of propagation of changes. If changes are made to master & slave at the same time , it is synchronous If changes are queued up  & written later , it is asynchronous