NoSQL Interview Preparation Guide
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NoSQL frequently Asked Questions in various NoSQL job Interviews by interviewer. The set of questions here ensures that you offer a perfect answer posed to you. So get preparation for your new job hunting

26 NoSQL Questions and Answers:

1 :: What is Not Only SQL (NoSQL)?

A NoSQL or Not Only SQL database provides a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases. Motivations for this approach include simplicity of design, horizontal scaling and finer control over availability. The data structure differs from the RDBMS, and therefore some operations are faster in NoSQL and some in RDBMS.
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2 :: Can you please explain the difference between NoSql vs Relational database?

The history seem to look like this:

Google needs a storage layer for their inverted search index. They figure a traditional RDBMS is not going to cut it. So they implement a NoSQL data store, BigTable on top of their GFS file system. The major part is that thousands of cheap commodity hardware machines provides the speed and the redundancy.

Everyone else realizes what Google just did.

Brewers CAP theorem is proven. All RDBMS systems of use are CA systems. People begin playing with CP and AP systems as well. K/V stores are vastly simpler, so they are the primary vehicle for the research.

Software-as-a-service systems in general do not provide an SQL-like store. Hence, people get more interested in the NoSQL type stores.

I think much of the take-off can be related to this history. Scaling Google took some new ideas at Google and everyone else follows suit because this is the only solution they know to the scaling problem right now. Hence, you are willing to rework everything around the distributed database idea of Google because it is the only way to scale beyond a certain size.
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3 :: Do you know how Cassandra writes?

Cassandra writes first to a commit log on disk for durability then commits to an in-memory structure called a memtable. A write is successful once both commits are complete. Writes are batched in memory and written to disk in a table structure called an SSTable (sorted string table). Memtables and SSTables are created per column family. With this design Cassandra has minimal disk I/O and offers high speed write performance because the commit log is append-only and Cassandra doesn’t seek on writes. In the event of a fault when writing to the SSTable Cassandra can simply replay the commit log
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4 :: Please tell me what is impedance mismatch in Database terminology?

It is the difference between the relational model and the in-memory data structures. The relational data model organizes data into a structure of tables and rows, or more properly, relations and tuples. In the relational model, a tuple is a set of name-value pairs and a relation is a set of tuples. All operations in SQL consume and return relations, which leads to the mathematically elegant relational algebra.
This foundation on relations provides a certain elegance and simplicity, but it also introduces limitations. In particular, the values in a relational tuple have to be simple—they cannot contain any structure, such as a nested record or a list. This limitation isn’t true for in-memory data structures, which can take on much richer structures than relations. As a result, if you want to use a richer in-memory data structure, you have to translate it to a relational representation to store it on disk. Hence the impedance mismatch—two different representations that require translation
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5 :: Do you have any idea about Aggregate-oriented databases?

An aggregate is a collection of data that we interact with as a unit. Aggregates form the boundaries for ACID operations with the database. Key-value, document, and column-family databases can all be seen as forms of aggregate-oriented database. Aggregates make it easier for the database to manage data storage over clusters. Aggregate-oriented databases work best when most data interaction is done with the same aggregate; aggregate-ignorant databases are better when interactions use data organized in many different formations.
Aggregate-oriented databases make inter-aggregate relationships more difficult to handle than intra-aggregate relationships. They often compute materialized views to provide data organized differently from their primary aggregates. This is often done with map-reduce computations.
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6 :: Do you know what is the key difference between Replication and Sharding?

a) Replication takes the same data and copies it over multiple nodes. Sharding puts different data on different nodes

b) Sharding is particularly valuable for performance because it can improve both read and write performance. Using replication, particularly with caching, can greatly improve read performance but does little for applications that have a lot of writes. Sharding provides a way to horizontally scale writes.
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7 :: What is Cassandra?

Cassandra is an open source scalable and highly available “NoSQL” distributed database management system from Apache. Cassandra claims to offer fault tolerant linear scalability with no single point of failure. Cassandra sits in the Column-Family NoSQL camp. The Cassandra data model is designed for large scale distributed data and trades ACID compliant data practices for performance and availability. Cassandra is optimized for very fast and highly available writes. Cassandra is written in Java and can run on a vast array of operating systems and platform.
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8 :: What is Pros?

a) Graph databases seem to be tailor-made for networking applications. The
prototypical example is a social network, where nodes represent users who have various kinds of relationships to each other. Modeling this kind of data using any of the other styles is often a tough fit, but a graph database would accept it with relish.

b) They are also perfect matches for an object-oriented system.
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9 :: What is Cons?

a) Because of the high degree of interconnectedness between nodes, graph
databases are generally not suitable for network partitioning.

b) Graph databases don’t scale out well.
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10 :: What is Cassandra Data Model?

The Cassandra data model has 4 main concepts which are cluster, keyspace, column, column family.

Clusters contain many nodes (machines) and can contain multiple keyspaces.

A keyspace is a namespace to group multiple column families, typically one per application.

A column contains a name, value and timestamp .

A column family contains multiple columns referenced by a row keys.
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