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  Improving the performance of AWS Glue jobs involves several strategies that target different aspects of the ETL (Extract, Transform, Load) process. Here are some key practices. 1. Optimize Job Scripts Partitioning : Ensure your data is properly partitioned. Partitioning divides your data into manageable chunks, allowing parallel processing and reducing the amount of data scanned. Filtering : Apply pushdown predicates to filter data early in the ETL process, reducing the amount of data processed downstream. Compression : Use compressed file formats (e.g., Parquet, ORC) for your data sources and sinks. These formats not only reduce storage costs but also improve I/O performance. Optimize Transformations : Minimize the number of transformations and actions in your script. Combine transformations where possible and use DataFrame APIs which are optimized for performance. 2. Use Appropriate Data Formats Parquet and ORC : These columnar formats are efficient for storage and querying, signif

10 Top NoSQL Database Recently Asked Interview Questions

10 Top NoSQL Database Recently Asked Interview Questions

1) Who is involved in developing NoSQL?

Amazon and Google Papers

2) What is NoSQL?

You can use NoSQL on non-relational databases. Like columnar databases, by using NoSQL, you can query data from non-relational databases.

3) What are the unique features of NoSQL databases?

  • no relationship between records
  • need Un-structural data
  • store data that individual records do not have a relationship with each other

4) How NoSQL-databases are faster than traditional RDBMS?

  • Stores database on multiple servers, rather than storing the whole database in a single server
  • Adding replicas on other servers, we can retrieve data faster even one of the servers crashes

5) What are the UNIQUE features of NoSQL?

  • Opensource
  • ACID complaint

6) What are the characteristics of a good NoSQL product?

  • High availability: Fault tolerance when a single server goes down
  • Disaster recovery: For when a data center goes down, or more likely, someone digs up a network cable just outside the data center
  • Support: Someone to stand behind a product when it goes wrong 
  • Services: Product experts who can advise on best practices and help determine how to use a product to address new or unusual business needs
  • Ecosystem: Availability of partners, experienced developers, and product information — to avoid being locked into a single vendor's expensive support and services contract

7) Reasons to go for NoSQL databases?

An RDBMS can not fit all of the enterprise requirements.

  • Big data
  • Schema Redesign overhead
  • Unstructured data explosion
  • It avoids Sparse data problems (RDBMS will use space for NULL values. But, NoSQL will ignore NULL values)
  • Dynamically changing relationships between attributes

8) Benefits of NoSQL?

  • Faster solutions for new generation problems
  • Lower cost
  • Modern computer systems don't exist in a vacuum; they always communicate with someone or something. NoSQL databases use in search engines to semantic web technologies and Hadoop. Leveraging these technologies can make the deployment of NoSQL productive & useful.

9) How many core types of NoSQL databases?


Extension to traditional table structures. Supports variable sets of columns (column families) and is optimized for column-wide operations (such as count, sum, and mean average).


Simple structure. Sets of named keys and their value(s), typically an uninterpreted chunk of data. Sometimes that simple value may be a JSON or binary document.


 A single fact is represented by three elements:

  • The subject you're describing
  • The name of its property or relationship to another subject
  • The value is either an intrinsic (such as an integer) or a unique ID. For example, Adam likes Cheese. Adam is the subject, and Cheese is the object.


XML, JSON, text, or binary blob. Any treelike structure. It can represent as an XML or JSON document. An order, for instance, includes a delivery address, billing details, and a list of products and quantities.

10) What are the most modern databases?

In-memory and flash databases

  • Great advances happened in real-time online transaction processing (OLTP) and analytics using in-memory databases. 
  • In-memory databases are specialized and targeted to particular problem domains. 
  • NoSQL databases take advantage of flash or memory caching to aid real-time analytics.


NoSQL software such as Oracle NoSQL, MarkLogic, Microsoft's Document DB, and IBM Cloudant, though.


This is a new database-access paradigm. It applies the software design lessons of NoSQL to RDBMS, creating a new breed of products, which is a great idea. But these products still use traditional relational math and structures. So they aren't being used. 


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