Are you preparing for the AWS DynamoDB interview? Are you sure you have covered all the basic and advanced-level questions? If not, then our guide on AWS DynamoDB interview questions will help you crack the interview. In this blog, we have listed AWS DynamoDB interview questions and answers prepared by the industry experts so that you can ace your interview.
A managed NoSQL database service, Amazon DynamoDB offers quick and predictable performance along with seamless scalability. By using DynamoDB, you can delegate the administrative tasks associated with running and scaling a distributed database, freeing you from having to worry about hardware provisioning, setup, software patching, replication or cluster scalability. Additionally, DynamoDB provides encryption at rest, which removes the operational complexity and burden of protecting sensitive data.
Now that you know what AWS DynamoDB is, let us learn some less-known facts about it:
The demand for AWS DynamoDB is quite high and therefore, the opportunities are quite vast. We assure you that the interview questions will assist you in acing the interview and getting the dream job and role.
We have categorized AWS DynamoDB Interview Questions into 3 levels they are:
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The four scalar data types that DynamoDB supports are as follows:
Data types for collections that DynamoDB supports include:
Quick in-place atomic notifications are supported by Amazon DynamoDB, allowing you to add or eliminate lists, sets or maps while also incrementing and decrementing a numeric attribute with just one API call.
You must specify a condition in order for a procedure to be finished on an item. A condition expression which can be created from the following is one you can define:
Crafted for internet application domains, Amazon DynamoDB is a quick and scalable NoSQL database provider that is also highly recommended. It maintains predictable high performance and is extremely cost-effective for caseloads of any scale.
Although it has scaling restrictions, Amazon SimpleDB is a good choice for smaller caseloads that demand query flexibility.
At the expense of performance and scale, it supports query flexibility and instantaneously indexes all item attributes.
The term "global Secondary index" refers to an index with a partition and divided key that differs from those on the table.
In the context that questions on the index could indeed cover every item in a table throughout all partitions, it is regarded as being "global."
Amazon DynamoDB supports a pair of index types. As follows:
The console or an API call can be used to remove a Global Secondary Index.
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Per table, a maximum of 5 global associated increases are permitted.
The API calls that Global Secondary Index supports are "Query" and "Scan."
There can be a maximum of five local associated increases per table.
Currently, once local secondary indexes are created, Amazon DynamoDB is unable to remove them from the table; however, the entire table can be deleted.
Once you establish a table to local secondary indexes, you can define a sort key element that isn't currently used to set up a local secondary index for use in the future.
This means that adding local secondary indexes to the existing table is likely impossible right now.
The group of characteristics which are copied or predicted from a table to an index are called projections. They are in addition to the automatically projected index key attributes and primary key attributes. The characteristics that are estimated into the index must always be specified when defining a local secondary index. Each index has a minimum of three of the following attributes:
It supports GET/PUT operations using the user-specified primary key. The ability to query a non-primary key attribute using both local and global secondary indexes promotes flexible querying.
Atomic counters are a feature of DynamoDB that let you change the value of an established attribute without affecting other write requests by using the update method. It increases the value of this characteristic by one each time the programme is executed.
Several advantages of DynamoDB over conventional SQL databases. You don't have to worry about providing or managing servers because it is a completely managed service. Second, you could indeed quickly increase or decrease ability as needed because it is highly scalable. Finally, you can be sure that your data is secure because it has built-in compliance and security features.
A managed NoSQL database service, DynamoDB provides quick, predictable performance with easy scalability. Several significant aspects set DynamoDB apart from other well-liked NoSQL implementations:
Any application that requires latency access to data and is willing to give up some data modeling flexibility in exchange for performance should consider DynamoDB. Additionally, it is a wise choice for programs that need to be highly available and are willing to give up some performance to achieve it.
Although DynamoDB is a strong tool, it does have some drawbacks. Its inability to handle large amounts of information is one of its limitations. You might want to think about a different solution if you need to store a lot of data. You should compare the costs of using DynamoDB with the advantages it offers because it can be costly to use.
The Query or Scan APIs can be used to access data stored in DynamoDB. The Scan API enables you to browse through data for items that meet specific criteria, whereas the Query API enables you to ask a series using a primary key.
You can record data changes in one's DynamoDB table in almost real-time using DynamoDB Streams, a feature of DynamoDB. This can be helpful for a variety of purposes, such as auditing or maintaining a backup copy of your data in a different location for disaster recovery.
You can record data adjustments done to goods in a DynamoDB table using a feature called DynamoDB Streams. Then, you can take action with that data by retrieving, filtering, or trying to export it to a different DynamoDB table, among other actions.
It is possible to use DynamoDB to connect data stored in AWS S3. But to do that, you'll need to use an API designed specifically for DynamoDB.
The Amazon.com website, the Kindle Fire tablet line, and the Amazon Web Services cloud computing service are a few real examples of applications that use DynamoDB as their main database.
If you're going to look for a controlled NoSQL database that scales well, DynamoDB is a fantastic choice. Additionally, if you require precise control over your data, it is a wise choice. If you want a controlled NoSQL database that is feature-rich and simple to use, Firebase is a good choice.
[ Related Article: MongoDB vs DynamoDB ]
Sort credentials are used to choose the order wherein items are kept within a partition, while separation keys are used to ascertain what partition an item would be stored in. A DynamoDB table can be searched for items using separation keys and sort keys combined.
The capacity to query the DynamoDB data using a different sort key from the one used to shop the data in the table is provided by local secondary indexes. If you want to query the data in a variety of ways or if you need to, this can be helpful.
DynamoDB's provisioned throughput feature enables users to specify the read and write capacity needs for their table. The user can then make sure that one‘s table can accommodate the volume of traffic they anticipate.
A technique for making sure that all duplicates of a data item are updated is the eventual consistency model. In distributed applications, where it may take some time for adjustments to reach every node, it is frequently used. According to the eventual consistency model, if enough time passes, all copies of a data item will have been updated.
Applications will encounter errors if they try to read or write greater than the maximum number of request units per second allowed. The application will need to increase its allotted request units or decrease the number of queries it is currently making.
By enabling you to clearly state conditions on write operations that need to be met in order for the write to be successful, DynamoDB uses conditional writes to help enhance efficiency. By doing this, you can prevent overwriting data which has already been revised by another process or writing duplicate data.
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It is a NoSQL database provider that is well-designed, offers quick and unavoidable performance, and scales easily. Additionally, it allows users to delegate running and scaling online digital content distribution to AWS for the users' convenience, so they won't need to worry about setup, configuration, hardware requirements, replication, bandwidth capacity planning, cluster scaling, or software patching.
The following is a list of some advantages of using Amazon DynamoDB:
The NoSQL databases used in non-relational databases. These databases are divided into four groups, which are as follows:
You just pay for the assets you provision in Amazon DynamoDB. Start out with DynamoDB's free tier limitations, which power many applications. Depending on the kind of resources you need, there are different monthly prices when you're in need of them.
It serves as DynamoDB's entry point. The DynamoDB Mapper class allows users to connect to a DynamoDB endpoint, allowing them to execute questions and scan against tables as well as carry out CRUD operations on items and access their data in various tables.
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It is a database service that offers and facilitates the storing, updating, and querying of objects that are recognised using key and value pairs and make up the actual material that is being stored.
Using DynamoDB, a global value with respect or a DynamoDB can automatically scale up and down in terms of read and write capacity.
Multiple items all over multiple tables can be added, removed, or replaced using the Amazon DynamoDB BatchWriteItem in just one request, but not in a single transaction. It supports inserting or deleting combinations of up to 25 items with a total combined request size of 16 MB.
You can generate an access key and a secret key by creating a user in AWS IAM which is Identity Access Management.
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It is possible to share this class across threads and it is thread-safe. DynamoDBMapper will start chucking DynamoDBMappingException while using the load, save and delete methods to demonstrate that domain courses are incorrectly marked or otherwise incompatible with this class.
Key-value and document data models are supported by the NoSQL database Amazon DynamoDB. The use of DynamoDB by developers allows them to create serverless, modern applications that can scale globally and support petabytes of data as well as tens of millions of read and write requests per second. High-performance, internet-scale applications that would tax conventional relational databases can run on DynamoDB.
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Madhuri is a Senior Content Creator at MindMajix. She has written about a range of different topics on various technologies, which include, Splunk, Tensorflow, Selenium, and CEH. She spends most of her time researching on technology, and startups. Connect with her via LinkedIn and Twitter .
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