Showing posts with label database. Show all posts
Showing posts with label database. Show all posts

April 21, 2022

Top 20 AWS DynamoDB Interview Questions and Answers

  

        Amazon Amazon Web Services' DynamoDB service is a proprietary NoSQL database service. It uses synchronous replication across many data centres to handle key-value and document data structures for all of its data services. DynamoDB has a high level of durability and availability as a result of this. Users of DynamoDB can additionally take advantage of Auto Scaling. DynamoDB automatically scales the database when it is enabled. DyanamoDb's primary data structures are hashing and B-trees. Data is first distributed using hashing into multiple divisions in the first entry. DynamoDB is compatible with a variety of languages, including Java, JavaScript, Node.js, Go, C#.NET, Perl, PHP, Python, Ruby, and many others.


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Ques. 1): What are the main advantages of DynamoDB?

Answer:

DynamoDB offers us a number of advantages, including consistency, availability, and partition tolerance. It provides facilities to easily store the graph data, which is not available to SQL.

Below are the major advantages of DynamoDB

Scalable: Virtual unlimited storage, users can store infinity amount of data according to their need

Cost Effective: It seems to be cutting costs, while a big part of data is able to migrate from SQL to NOSQL. Basically it charges for reading, writing, and storing data along with any optional features you choose to enable in DynamoDB


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Data Replication: All data items are stored on SSDs and replication is managed internally across multiple availability zones in a region or can be made available across multiple regions.

DynamoDB is a serverless database that scales horizontally by distributing a single table over several servers.

Easy Administration: Because Amazon DynamoDB is a fully managed service, you won't have to worry about hardware or software provisioning, setup and configuration, software patching, or partitioning data across several instances as you scale.

Secure: Customizable traffic filtering, Regulatory Compliance Automation, Database Threat Detection, and Advanced Notification and Reporting System


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Ques. 2): What does the DynamoDBMapper class entail?

Answer:

The DynamoDBMapper class provides access to Amazon DynamoDB. It gives you access to a DynamoDB API and lets you access your data across several tables. It also allows you to run queries and scans against tables, as well as perform different create, read, update, and delete (CRUD) activities on objects.


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Ques. 3): What are disadvantages of DynamoDB?

Answer:

The disadvantages of DynamoDB are as follows-

  • Deployable only on AWS and cannot be installed on individual desktops/servers
  • Queries - Querying data is extremely limited
  • Table Joins- Joins are impossible
  • No Triggers
  • No foreign keys concept to refer to other table items
  • No server side scripts


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Ques. 4): Is DynamoDB a SQL database?

Answer:

DynamoDB is a NoSQL database that can manage structured and semi-structured data, as well as JSON documents. DynamoDB smoothly scales to handle massive volumes of data and a large number of users.

SQL is the industry standard for data storage and retrieval. Although relational databases include a variety of tools for facilitating the building of database-driven applications, they always employ SQL.


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Ques. 5): What distinguishes Amazon DynamoDB from Amazon Aurora?

Answer:

Aurora is a relational database service, whereas DynamoDB is a NoSQL database service.

For data manipulation and retrieval, Aurora employs SQL, but DynamoDB uses a unique syntax.

In Aurora, horizontal partitioning is used, whereas in DynamoDB, sharding is used.

DynamoDB implements key-value and document models, while Aurora uses a relational database management system.

DynamoDB does not support server-side scripting, although Aurora does.


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Ques. 6): What are the data types supported by DynamoDB?

Answer:

DynamoDB supports a large set of data types for table attributes. Each data type falls into one of the three following categories -

  • Scalar - These types represent a single value, and include number, string, binary, Boolean, and null.
  • Document - These types represent a complex structure possessing nested attributes, and include lists and maps.
  • Set - These types represent multiple scalars, and include string sets, number sets, and binary sets.


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Ques. 7): What is the DynamoDB Query functionality and how does it work?

Answer:

In DynamoDB, you have two choices for accessing data from collections: Query and Scan. Scan searches the whole database for records that match the criteria, whereas Query performs a direct lookup for a specified data set based on key restrictions.

In addition to the main key, DynamoDB uses a global secondary key, a local secondary key, and a partition primary key to improve read/write speed.

As a result, it is faster and more efficient than the DynamoDB Scan function, and it is recommended for most data retrieval applications.


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Ques. 8): How does DynamoDB protect data from being lost?

Answer:

DynamoDB has long-term storage and a two-tier backup strategy to prevent data loss to a minimum. Each participant has three nodes, each of which holds the same data from the partition. In addition, a B tree is used to locate data, and a replication log is used to track changes in each node. DynamoDB takes snapshots of these and keeps them for a month in another AWS database in case data restoration is required.


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Ques. 9): What are DynamoDB's secondary indexes?

Answer:

A secondary index is a data structure that stores a portion of a table's properties, as well as an alternate key for Query operations. Query can be used to retrieve data from the index in the same way it can be used to retrieve data from a table.


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Ques. 10): What does Data Pipeline do?

Answer:

Data Pipeline exports and imports data from S3 bucket, file, etc.It also helps in backups, testing, and for similar needs.

There are 2 types Data Pipeline:

DataPipelineDefaultRole - contains all the ations you permit the pipeline to perform.

DataPipelineDefaultResourceRole - contains all the resources you permit the pipeline to perform.


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Ques. 11): List some important methods of Dynamo DB Mapper Class?

Answer:

  • Save: Saves a particular object to the table.
  • Load: Retrieves an item from the table
  • Delete: It deletes an item from the table
  • Query: Queries a table or an index
  • Scan page: Scans a table or index and returns a matched result page.
  • Parallel scan: Performs a scan of the entire table or index.
  • Batch save: Saves object to one or more tables.


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Ques. 12): Is it safe to use DynamoDBMapper in a thread?

Answer:

This class is thread-safe and can be shared across many threads. DynamoDBMapper will throw DynamoDBMappingException while using the save, load, and delete methods to indicate that domain classes are wrongly annotated or otherwise incompatible with this class.


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Ques. 13): Are DynamoDB's write operations atomic?

Answer:

DynamoDB supports atomic counters, which allow you to add or decrement the value of an existing attribute without interfering with other write requests by using the update method. This attribute is incremented by one each time the application is run.


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Ques. 14): Does Amazon DynamoDB support conditional operations?

Answer:

For an operation to be completed on an item, you have to specify a condition.

You can define a ConditionExpression that can be constructed from the following:

Boolean functions: ATTRIBUTE_EXIST, CONTAINS, and BEGINS_WITH

Comparison operators: =, <>, <, >, <=, >=, BETWEEN, and IN

Logical operators: NOT, AND, and OR.

You can also construct a free-form conditional expression that combines multiple conditional clauses which also includes nested clauses.


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Ques. 15): What are the differences between Amazon SimpleDB and Amazon DynamoDB?

Answer:

Amazon DynamoDB: It is a highly recommended fast and scalable NoSQL Database Service that is designed for internet scale applications, maintains predictable high performance, and is highly cost-effective for workloads of any scale.

Amazon SimpleDB is an excellent fit for lower workloads that require query flexibility, but it has scaling limits.

It indexes all item attributes automatically and allows for query flexibility at the expense of performance and scale.


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Ques. 16): In Amazon DynamoDB, how do you delete a Global Secondary Index?

Answer:

The console or an API request can be used to delete a Global secondary index.

On the console, choose the table from which you wish to delete the Global Secondary index, then go to the "indexes" tab under "Table items," select the "indexes" tab, and then click the "Deletion" button next to the delete index.

The Update Table API call can also be used to delete a Global Secondary Index.


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Ques. 17): What is use of Scan operation in DynamoDB?

Answer:

A Scan operation in Amazon DynamoDB reads every item in a table or a secondary index. By default, a Scan operation returns all of the data attributes for every item in the table or index. You can use the ProjectionExpression parameter so that Scan only returns some of the attributes, rather than all of them.


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Ques. 18): What type of query capabilities does DynamoDB provide?

Answer:

GET/PUT operations in DynamoDB are supported by a user-defined primary key. The primary key is the sole attribute that objects in a database must have. When you construct a table, you specify the primary key, which uniquely identifies each item. DynamoDB also allows for flexible querying by allowing you to use global secondary indexes and local secondary indexes to query on nonprimary key properties.


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Ques. 19): What are DynamoDB streams, and how do you use them?

Answer:

DynamoDB Streams is a robust service that may be used in conjunction with other AWS services to solve a variety of challenges. When we enable DynamoDB Streams, it records a time-ordered sequence of item-level alterations in a DynamoDB table and saves the data for up to 24 hours.


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Ques. 20): What are projections and how do they work?

Answer:

The set of properties that are transferred or projected from a table to an index is known as projections.

They're in addition to the index key and main key qualities, which are projected automatically. When creating a local secondary index, you must first define the properties that will be projected into the index. Each index has a minimum of three properties, which are:

  • The value of the table partition key
  • The attribute that will be used as the index sort key.
  • Sort by key value in the table


AWS Database Interview Questions and Answers




April 19, 2022

Top 20 AWS Aurora Interview Questions and Answers

 

AWS Aurora is an Amazon cloud-based managed database service. This is one of the most extensively utilised data storage and processing services for low latency and transactional data. The AWS aurora service combines the benefits of open source databases such as MySQL and PostgreSQL with enterprise-level dependability and scalability. For efficient data availability, it uses a clustered technique with data replication in the AWS availability zone. It is much faster than native MySQL and PostgreSQL databases, and it requires little server maintenance. It has a large storage capacity and can expand up to 64 Terabytes of database size for enterprise use.


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Ques. 1): What is Amazon Aurora and how does it work?

Answer:

AWS Aurora is a cloud-based relational database that combines the performance and availability of typical enterprise databases with the ease of use and low cost of open source databases. It's five times faster than a typical MySQL database, and three times faster than a standard PostgreSQL database.

AWS Aurora helps provide commercial databases with security, availability, and dependability. It is fully managed by AWS Relational Database Service (RDS), which automates time-consuming administration activities including hardware provisioning, database setup, patching, and backups. It's a fault-tolerant, self-healing storage system that auto-scales up to 128TB per database instance and provides high performance and availability with up to 15 low-latency read replicas, point-in-time recovery, continuous backup to Amazon S3, and replication across three Availability Zones, among other features (AZs).


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Ques. 2): What are Amazon Aurora DB clusters, and what do they do?

Answer:

An Amazon Aurora DB cluster is made up of one or more database instances and a cluster volume that stores the data for those databases.

An Aurora cluster volume is a virtual database storage volume that spans multiple Availability Zones and contains a copy of the DB cluster data in each. There are two sorts of database instances in an Aurora DB cluster:

Primary DB instance: Supports read and write operations and handles all data modifications to the cluster volume. There is only one primary DB instance in each Aurora DB cluster.

Aurora Replica: It connects to the same storage disc as the primary DB instance and only enables read operations. Each Aurora DB cluster can contain up to 15 Aurora Replicas in addition to the original DB instance. Aurora automatically switches to an Aurora Replica if the primary DB instance becomes unavailable. The Aurora Replicas' failover priority can be set. Aurora Replicas can also transfer read workloads from the primary DB instance.


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Ques. 3): What are the benefits of using Aurora?

Answer:

The following are some of Aurora's benefits:

Enterprise-level security: Because Aurora is an Amazon service, you may be confident in its security and use the IAM capabilities.

Enterprise-level availability: It is ensured by multiple replications of database instances across several zones.

Enterprise-level scalability: With Aurora serverless, you can configure your database to scale up and down dynamically in response to application demand.

Enterprise-level performance: Open-source DB's simplicity and cost-effectiveness.

Aurora is interoperable with MySQL and PostgreSQL at the enterprise level. If your present application is built on MySQL or PostgreSQL, you can move it or utilise Amazon RDS to convert your database to Aurora Engine.

AWS Management Console: Amazon Management Console is easy to use with click and drag features to quickly set-up your Aurora Cluster.

Maintenance: Aurora has almost zero server maintenance. 5 times faster than MySQL and 3 times faster than PostgreSQL.


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Ques. 4): What are Aurora's advantages?

Answer:

The following are some of the advantages of AWS Aurora:

High Performance and Scalability – We can quickly scale up and down our database deployment from a smaller to a larger instance.

Fully Managed - Because Amazon Relational Database Service (RDS) manages Aurora, we don't have to bother about database management activities like hardware provisioning, software patching, setup, configuration, or backups.

Highly Secure - Aurora is very secure, with various levels of security for your database.

Support for Database Migrations to the Cloud - Aurora is utilised as an attractive target for database migrations to the cloud.

MySQL and PostgreSQL Compatible - Aurora is entirely compatible with existing MySQL and PostgreSQL open source databases, and support for new releases is added on a regular basis.

High Availability and Durability - Aurora's high availability and durability make it simple to recover from physical storage failures.


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Ques. 5): How Aurora Works?

Answer:

Primary DB and Aurora replica DB, as well as a cluster volume to handle the data for those DB instances, make up an Aurora DB cluster. Aurora cluster volume is a virtual database storage volume that spans multiple Availability Zones in order to better support global applications. The DB cluster data is duplicated in each zone.

All read and write operations are performed over cluster volume in the primary database. Each Aurora cluster will have one primary database instance.

It's just a copy of the primary database instance whose sole purpose is to provide data, i.e. solely read operations. To provide high availability in all Zones, a primary DB instance can have up to 15 replicas. In a fail-safe circumstance, Aurora will switch to a replica when a Primary DB is not accessible. Replicas aid in the reduction of read workload on the primary database. For replicas, you can set the priority of failover.

Aurora can have a multi-master cluster as well. All DB instances in a multi-master setup will be able to read and write data. In AWS language, these are known as reader and writer DB instances, and we can call this a multi-master replication.

You can also set up Amazon S3 to keep a backup of your database. Even in the worst-case scenario, where the entire cluster is down, your database remains safe.

You can utilise Aurora Serverless to automatically start scaling and shutting down the database to fit application demand for an unpredictable workload.


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Ques. 6): What are the advantages of using Amazon RDS with MySQL?

Answer:

Amazon RDS for MySQL has the following advantages:

Easy, managed deployments - : Simple, managed deployments are used to quickly launch and connect to a production-ready MySQL database.

High availability and read replicas - High availability and read replicas are utilised to ensure that our MySQL databases are available and durable.

Fast, dependable storage - utilised to provide two SSD-backed MySQL database storage alternatives.

Monitoring and metrics - Amazon RDS Enhanced Monitoring gives you access to more than 50 CPU, RAM, file system, and disc I/O metrics.

Backup and recovery - utilised to ensure that our MySQL database instance can be recovered.

Isolation and security – used to ensure that our MySQL databases are kept secure.


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Ques. 7): What is the relationship between Aurora and Amazon RDS Engines?

Answer:

The following points will demonstrate how Amazon RDS' standard engines, such as MySQL and PostgreSQL, interact with Aurora:

When creating new database servers with Amazon RDS, you can select Aurora as a database engine.

If you're acquainted with Amazon RDS, Aurora should be simple to set up. You can utilise the Amazon RDS administration console to set up Aurora clusters, as well as the CLI commands and API to perform database maintenance activities like backup, recovery, and repair.

Aurora's automatic clustering, replication, and other administration operations are controlled over the entire cluster of database servers, not just one instance, allowing you to manage big MySQL and PostgreSQL servers efficiently and at a cheap cost.

Data from Amazon RDS for MySQL and PostgreSQL can be replicated or imported into Aurora using snapshots. Another feature is push-button migration, which may be used to migrate your Amazon RDS MySQL and PostgreSQL databases to Aurora.


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Ques. 8): What are Endpoints and How Do I Use Them?

Answer:

When a user connects to an Aurora cluster, an endpoint is a combination of host name and port.

Endpoints are divided into four categories:

Cluster Endpoint: Cluster Endpoint is used to connect to the current primary database instance and to assist with write operations.

Custom endpoint: A custom endpoint is used to represent a set of DB instances selected by the user.

Reader Endpoint: Reader Endpoint is a read-only endpoint used to connect Aurora replicas.

Instance Endpoint: Instance Endpoint is used to connect to a specific database instance and to diagnose problems with capacity or performance in that instance.


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Ques. 9): How can we associate a IAM Role with an Aurora Cluster using CloudFormation?

Answer:

PostRunCommand:

  Description: You must run this awscli command after the stack is created and may also need to reboot the cluster/instance.

  Value: !Join [" ", [

    "aws rds add-role-to-db-cluster --db-cluster-identifier",

    !Ref AuroraSandboxCluster,

    "--role-arn",

    !GetAtt AuroraS3Role.Arn,

    "--profile",

    !FindInMap [ AccountNameMap, !Ref AccountNamespace, profile ]

  ]]


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Ques. 10): What are AWS Aurora's limitations?

Answer:

If you need additional features or have an older version of MySQL, you won't be able to use it because it only supports MySQL-5.6.10. Amazon will add new MySQL functionality to Aurora in the future, but you'll have to wait.

Because Aurora currently only supports InnoDB, you won't be able to use MyISAM tables.

With Aurora, you don't have the choice of using smaller RDS than r3.large.


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Ques. 11): Is it possible for my application to fail over to the cross-region replica from my current primary?

Answer:

Yes, you can use the Amazon RDS console to promote your cross-region replica to the new primary. The promotion process for logical (binlog) replication takes a few minutes, depending on your workload. When you start the promotion process, the cross-region replication will halt.

You may promote a secondary region to take full read/write workloads in under a minute with Amazon Aurora Global Database.


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Ques. 12): What is Amazon RDS for MySQL and how does it work?

Answer:

AWS RDS for MySQL manages time-consuming database management activities including backups, software patching, monitoring, scaling, and replication, allowing you to focus on application development.

It is compatible with Amazon RDS Community Edition versions.


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Ques. 13): What does it mean to be "MySQL compatible"?

Answer:

Amazon Aurora is plug-and-play compatible with existing MySQL open-source databases, and new releases are added on a regular basis. This implies that using conventional import/export tools or snapshots, you can quickly move MySQL databases to and from Aurora. It also means that the majority of the code, apps, drivers, and utilities you already use with MySQL databases can be utilised with Aurora with little or no modification. When comparing Aurora with MySQL, keep in mind that the Amazon Aurora database engine is designed to be wire-compatible with MySQL 5.6 and 5.7, which uses the InnoDB storage engine. This makes switching applications between the two engines a breeze. Amazon Aurora does not support certain MySQL capabilities, such as the MyISAM storage engine.


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Ques. 14): How can I switch from MySQL to Amazon Aurora and back?

Answer:

There are various options available to you. To export data from MySQL and to import data into Amazon Aurora, use the normal mysqldump and mysqlimport utilities, respectively. You can also utilise the AWS Management Console to move an Amazon RDS for MySQL DB Snapshot to Amazon Aurora utilising Amazon RDS's DB Snapshot migration feature. Most customers have their migration completed in under an hour, while the time varies on the type and amount of the data set.


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Ques. 15): What does it mean to have "five times the performance of MySQL"?

Answer:

By tightly integrating the database engine with an SSD-based virtualized storage layer purpose-built for database workloads, Amazon Aurora improves MySQL performance by lowering writes to the storage system, avoiding lock contention, and eliminating delays caused by database process threads. Amazon Aurora offers over 500,000 SELECTs/sec and 100,000 UPDATEs/sec, five times faster than MySQL running the same benchmark on the same hardware, according to our tests with SysBench on r3.8xlarge instances.


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Ques. 16): What are the best practises for optimising my database workload for Amazon Aurora PostgreSQL-Compatible Edition?

Answer:

Amazon Aurora is designed to be PostgreSQL compatible, allowing existing PostgreSQL applications and tools to run without needing to be modified. However, Amazon Aurora outperforms PostgreSQL in the domain of highly concurrent workloads. We recommend building your applications to support a large number of concurrent queries and transactions in order to maximise your workload's throughput on Amazon Aurora.


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Ques. 17): What are the options for scaling the compute resources associated with my Amazon Aurora DB Instance?

Answer:

By selecting the desired DB Instance and clicking the Modify button in the AWS Management Console, you can scale the compute resources allocated to your DB Instance. Changing the DB Instance class modifies memory and CPU resources.

When you make modifications to your DB Instance class, they will be applied during the maintenance window you specify. You can also utilise the "Apply Immediately" flag to have your scaling requests applied right away. Both of these approaches will have a short-term impact on availability while the scaling operation is carried out. Remember that any other pending system modifications will be applied as well.


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Ques. 18): What is my plan of action if my database fails?

Answer:

Amazon Aurora keeps six copies of your data across three Availability Zones (AZs) and will attempt to recover your database in a healthy AZ without losing any data. You can restore from a DB Snapshot or perform a point-in-time restore procedure to a fresh instance if your data is unavailable within Amazon Aurora storage. For a point-in-time restoration procedure, the latest restoreable time can be up to five minutes in the past.


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Ques. 19): Is it possible for me to share my photos with another AWS account?

Answer:

Yes. Aurora allows you to take snapshots of your databases, which you may then use to restore them later. You can share a snapshot with another AWS account, and the receiving account's owner can use it to restore a database containing your data. You may even make your snapshots public, allowing anyone to restore a database containing your (public) data. You can use this capability to exchange data between different AWS accounts for different settings (production, dev/test, staging, etc.), as well as keep backups of all your data in a separate account in case your main AWS account is ever compromised.

 

Ques. 20): How does Amazon Aurora improve the fault tolerance of my database in the event of a disc failure?

Answer:

Amazon Aurora divides your database volume into 10 GB parts and distributes them over many discs. Your database volume is replicated six times, over three AZs, for each 10 GB piece. Amazon Aurora is built to handle the loss of up to two copies of data without affecting database write availability and up to three copies without affecting database read availability in a transparent manner. Amazon Aurora is also self-healing storage. Data blocks and drives are inspected for faults and corrected automatically on a regular basis.

 

 


November 23, 2021

Top 20 AWS Database Interview Questions and Answers

  

Ques: 1). What are your thoughts on the Amazon Database?

Answer: 

Amazon Database is an Amazon Web Services offering that includes managed databases, managed services, and NoSQL. It also comes with a fully managed petabyte-scale data warehouse and in-memory caching as a service. There are four AWS database services to choose from, and the user can use one or all of them depending on their needs. DynamoDB, RDS, RedShift, and ElastiCache are the Amazon database services.

 

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Ques: 2). What are the features of Amazon Database?

Answer: 

Following are the important features of Amazon Database:


  • Easy to administer
  • Highly scalable
  • Durable and reliable
  • Faster performance
  • Highly available
  • More secure
  • Cost-effective

 

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 Ques: 3). What is a key-value store, and how does it work?

Answer: 

A key-value store is a database service that makes it easier to store, update, and query items that are identified by their keys and values. These objects are made up of keys and values that make up the actual content that is saved.

 

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Ques: 4).  What Is A Data Warehouse, And How Can Amazon Redshift Help With Storage?

Answer: 

A data warehouse can be conceived of as a repository for data acquired and stored from the company's systems and other sources. As a result, a data warehouse's design is three-tiered:

The tools that clean and collect data are found on the bottom rung.

We have tools in the intermediate layer that use Online Analytical Processing Server to alter the data.

We have various tools on the top layer that execute data analysis and data mining on the front end.

Setting up and maintaining a data warehouse costs a lot of money, especially as an organization's data grows and its data storage servers need to be upgraded on a regular basis. As a result, AWS RedShift was created, allowing businesses to store their data in Amazon's cloud-based warehouses.

 

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Ques: 5). What Is The Difference Between A Leader Node And A Compute Node?

Answer: 

The queries from the client application are received in a leader node, where they are parsed and an execution plan is created. The stages for processing these queries are created, and the outcome is returned to the client application.

The steps allocated in the leader node are completed in a compute node, and the data is transferred. After that, the result is returned to the leader node before being delivered to the client application.

 

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Ques: 6). What Is Amazon ElastiCache, and How Does It Work?

Answer: 

Amazon ElastiCache is an in-memory key-value store that can handle Redis and Memcached as key-value engines. It is a fully managed and zero administration service that Amazon has hardened. You may use Amazon ElastiCache to either create a new high-performance application or upgrade an existing one. ElastiCache has a wide range of applications in gaming, healthcare, and other fields.

 

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Ques: 7). What Is Amazon ElastiCache's Purpose?

Answer: 

The caching of information that is utilised repeatedly could increase the performance of online applications. Using in-memory-caching, the data may be accessed very quickly. There is no need to manage a separate caching server with ElastiCache. An open source compatible in-memory data source with high throughput and low latency can be readily deployed or run.

 

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Ques: 8). When would I prefer Provisioned IOPS over Standard RDS storage?

Answer: 

Provisioned IOPS deliver high IO rates but on the other hand it is expensive as well. Batch processing workloads do not require manual intervention they enable full utilization of systems, therefore a provisioned IOPS will be preferred for batch oriented workload.

 

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Ques: 9). What Oracle features are available in AWS RDS?

Answer: 

Oracle is a well-known relational database that is available through Amazon RDS with enterprise version features. Almost every Oracle functionality may be used with the RDS platform.

If no version is specified when the database is created, it defaults to the most recent version available at the moment. In a Python SDK programme, here's an example of how to access the supported DB Engine versions using the AWS API.

 

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Ques: 10). What are the differences between Amazon RDS, DynamoDB, and Redshift?

Answer: 

Amazon RDS is a relational database management service that handles patching, upgrading, and data backups for you without requiring your involvement. RDS is a database management service that exclusively handles structured data.

On the other hand, DynamoDB is a NoSQL database service, which works with unstructured data.

Redshift is a data warehouse product that is utilised in data analysis and is a completely different service.


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Ques: 11). Can I use Amazon RDS to operate many database instances for free?

Answer: 

Yes. You can operate many Single-AZ Micro database instances, and they're all free! Any use of more than 750 instance hours across all Amazon RDS Single-AZ Micro DB instances, across all qualifying database engines and locations, will be paid at normal Amazon RDS charges. For example, if you run two Single-AZ Micro DB instances for 400 hours each in a month, you'll have 800 instance hours total, with 750 hours being free. The remaining 50 hours will be charged at the usual Amazon RDS rate.


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Ques: 12). What is Oracle Licensing and how does it work?

Answer: 

Oracle licenses can be used in RDS in two ways:

Model with a License

The license for the software you'll use is held by Amazon in this model. Also, through its support programme, AWS provides support for both AWS and Oracle products. As a result, the user does not need to purchase a separate license. The user's licensing costs are included in the platform pricing.

Bring Your Own license

In this arrangement, the user imports her license into the RDS platform. It is the user's responsibility to keep the license, database instance class, and database edition all in sync. The user directly contacts the Oracle support channel for any need. In this model the supported editions are Enterprise Edition (EE), Standard Edition (SE), Standard Edition One (SE1) and Standard Edition Two (SE2).


AWS Simple Storage Service (S3) Interview Questions and Answers


Ques: 13). If I delete my DB Instance, what happens to my backups and DB Snapshots?

Answer: 

When you delete a database instance, you have the option of creating a final database snapshot, which you can use to restore your database. After the instance is removed, RDS keeps this user-made DB snapshot together with all other manually created DB snapshots. Automated backups are also deleted, leaving just manually created DB Snapshots.


AWS Fargate Interview Questions and Answers


Ques: 14).  How can I load data into Amazon Redshift from various data sources such as Amazon RDS, Amazon DynamoDB, and Amazon EC2?

Answer: 

You have two options for loading the data:

The COPY command can be used to load data into Amazon Redshift in parallel from Amazon EMR, Amazon DynamoDB, or any SSH-enabled server.

AWS Data Pipeline is a fault-tolerant, high-performance solution for loading data from a range of AWS data sources. To load your data into Amazon Redshift, you can utilise AWS Data Pipeline to specify the data source, required data transformations, and then run a pre-written import script.


AWS SageMaker Interview Questions and Answers


Ques: 15). What is an RDS instance, and how does it work?

Answer: 

The Amazon Relational Database Service (Amazon RDS) is a web service that lets you easily construct a cloud-based relational database instance. Amazon RDS administers the database instance on your behalf, including backups, failover, and database software maintenance. Read Replicas, which are RDS instances that act as copies of the source master database for handling read-requests, can be launched for read-heavy applications. A source DB instance can have up to five (5) Read Replicas attached to it. The existing RDS Instances in the selected AWS region are listed on the Instances page. The information for an existing RDS Instance are displayed when you click on it.

Fields

Name - unique name/identifier for the RDS instance.

Engine - The version of the MySQL or Oracle engine of the RDS Instance.

RDS Subnet Group - The group of RDS Subnets for the VPC.

Availability Zone - The availability zone into which the RDS Instance will be created and launched.

Multi-AZ - Indicates that the RDS Instance will be used in a multiple availability zone configuration.

Instance class - If you selected a different instance type, the existing instance will be terminated and new RDS instance will be launched.

Storage - storage size in GBs for the instance that will be allocated for storing data.

Source instance - If the instance is a Read Replica, it will list the name of the source DB instance.

Status - The status of the RDS Instance (creating, modifying, available, rebooting, deleting). An RDS Instance will only be accessible when its status is 'available'.

 

AWS DynamoDB Interview Questions and Answers 



Ques: 16). What is Amazon Aurora and how does it work?

Answer: 

Amazon Aurora is a form of cloud-based relational database that works with MySQL and PostgreSQL. It performs five times faster than MySQL and three times faster than PostgreSQL. The performance and availability of traditional databases are combined with the simplicity and cost-effectiveness of open-source databases in this hybrid database type. Because Amazon RDS manages this database completely, operations like hardware provisioning, database setup, patching, and backups are all automated.


AWS Elastic Block Store (EBS) Interview Questions and Answers


Ques: 17). Which Amazon Web Services services will you use to collect and process e-commerce data in real time for analysis?

Answer: 

For real-time analysis, I'll utilise DynamoDB to collect and handle e-commerce data. DynamoDB is a fully managed NoSQL database service for unstructured data. It can even be used to extract e-commerce information from websites. RedShift may then be used to perform analysis on the retrieved e-commerce data. Elastic MapReduce can be utilised for analysis as well, but we won't use it here because real-time analysis isn't required.


AWS Amplify Interview Questions and Answers


Ques: 18). What happens if a user deletes a dB instance? What happens to the dB snapshots and backups?

Answer: 

The user is given the option of taking a last dB snapshot when a dB instance is removed. If you do so, your information from the snapshot will be restored. When the dB instance is removed, AWS RDS preserves all of the user-made dB snapshots together with all of the other manually created dB snapshots. Automated backups are erased at the same time, but manually produced dB snapshots are kept.


AWS Secrets Manager Interview Questions and Answers


Ques: 19). What Is A Dynamodbmapper Class And How Does It Work?

Answer: 

The DynamoDB's entry point is the mapper class. It allows users to access the endpoint and input the DynamoDB. Users can use the DynamoDB mapper class to retrieve data stored in various databases, run queries, scan them against the tables, and perform CRUD activities on the data items.


AWS Django Interview Questions and Answers


Ques: 20). What is the RDS interface, and how does it work?

Answer: 

To use the RDS service, Amazon provides an RDS interface. An RDS interface is required to interact with the RDS service, such as reading data, uploading data, and running other programmes.

The GUI Console, Command Line Interface, and AWS API are the three main interfaces available.

A GUI Console is the most basic interface via which users can interact with the RDS Service.

The Command Line Interface (CLI) provides you with CLI access to the service, allowing you to run DB commands and interact with it.

An AWS API is an Application Programming Interface that allows two systems to exchange data.


AWS Glue Interview Questions and Answers