Introducing the Key-Value Type Database in NoSQL

It turns out that all kinds of databases are used in the IT industry. In this article, we will talk about the Key-Value Database. Key-Value Database can be said to be the simplest form of a database offering tremendous performance.

Key-Value database

What is a Key-Value Database?

A key-value database is typically designed for storing, retrieving, and managing data in a way that the data structure is easily accessed and modified. One of these is called a dictionary.

Dictionaries include records, which contain numerous fields containing data of various types and values ranging from string to float. These records are then stored and accessed using a unique key that identifies and locates the data within the database. This is the fundamental operating principle of a key-value database, which is one of the NoSQL database types.

In its simplest form, a key-value store is like a dictionary as it exists in most programming paradigms but stored in a more reliable method.

Let us dive in deeper into the details of a key-value database.

FACT

Key-Value Stores appear as in-memory databases (that is, in the working memory) and as on-disk solutions (in fixed-disk storage).

Key-value databases are often considered as one of the simplest forms of NoSQL databases. This model’s simplicity makes key-value stores and databases quick and user-friendly

Advantages of Key-Value Database

A key-value store (which is not a database in the conventional sense) comprises a single search key that can be used only for identification searches. If you require data on any additional filter fields or a range search on the “key,” you must perform a sequential scan of the entire file.

Let's discuss both the advantage and the disadvantages of a key-value database
Let’s discuss both the advantages and the disadvantages of a key-value database. Source: DreamsTime

Key-value databases make use of small, efficient index structures to enable them to locate a value quickly and reliably by its key, making them perfect for systems that require data to be found and retrieved in real-time.

The key-value store has the advantage of allowing for practically continuous access to pairs even as the store grows. HashMap performs fundamental operations (get and put) in constant time, assuming the hash algorithm properly distributes the elements among the buckets.

This, of course, relies on a decent implementation of the method of your key. Furthermore, it can be partitioned really well, which can make retrievals very fast.

Downsides of Key-Value Database

The main concept (and one of the most important concepts) of a key-value database is that it does not care what kind of data is stored in the database. But, are there any downsides to this? Let us take a look.

Querying Method using Key: While this is the preferred method of querying information, it is also the ONLY method. What if this method is not appropriate for your application? Not to mention the fact that the keys are only applicable to particular sorts of data, not all. This goes beyond the loss of referential integrity, the absence of foreign keys, and the absence of transactions, as with the RDBMS.

Value is updated as a whole: Consider the following scenario: Someone wishes to update their last login credentials. When a client requests data, the search must be performed on the entire set of data, and after it is located, the entire set of data must be returned as a response. This is inefficient on a bigger scale.

Query: Fetching results in a typical tabular format is hard and expensive, as you must perform a JOIN for each attribute to get data from multiple rows. Additionally, it lacks a processing engine for query aggregation and grouping. Additionally, transactions are not supported, and joins must be performed in the application space.

Lookup: Not optimized for lookup as it requires scanning the entire set of values or creating separate index values. Moreover, there is no way to ensure that attribute names are spelt consistently and correctly.

Use Cases of Key-Value Database

When running an organisation or a business, it is often important to develop a technology stack that is reliable and scalable from the beginning. And one of the most important criteria is the type of database that will be used in a day to day scenario.

It has to be fast, easy and offers good performance as well as handle lots of users, depending on the use cases.

Since a key-value database is easily scalable, key-value can handle thousands upon thousands of users at any given second. There are a few situations where key-value shines:

  • Large scale session management
  • Product recommendations

The vast majority of programmes that use session management do so through the usage of key-value databases. They successfully manage session data for all newly created user-created mobile apps for smartphones and other devices.

The key-value database can also be utilised for enormous multi-player online games, which helps keep track of each player’s session.

Because of this, they are also superb at keeping shopping carts for online customers in check until the bill is due. It is recommended that a relational database better handles payment transactions and related income postings.

Moreover, a key-value database primarily powers product recommendations in an online store.

Most recommendations on e-commerce stored are powered by key-value databases
Most recommendations on e-commerce stored are powered by key-value databases. Source: Amazon

The shopping preference of the visitor or anyone who is viewing the site is stored as the value that belongs to the key. Then, the recommendations are performed using Machine Learning, which generates a set of recommended items based on the history of the past items that you have purchased on the e-commerce platform.

Using this data, product recommendations and advertising can be performed where the database holds personalised lists of items for individual customers.

Key-Value Database Examples

As some examples show below, there are various types of key-value databases. In reality, many key-value databases are likely to be known to a data scientist because they are among the most popular and widely-used databases available.

DynamoDB: Probably the most widely used key-value and document database. It serves as a hybrid between a document and a key-value database so it is not purely a key-value database (We will look into what is a document database in a future article)

Aerospike: Open-source database that is optimized for in-memory storage.

Berkeley DB: A high-performance yet relatively basic open-source database developed by Oracle.

Riak: Made for developing apps and works well with other databases and apps.

The key points to take away

Key-value databases locate a value by its key, making them ideal for systems that need to be able to find and retrieve data in constant time. To retrieve data, the data must be requested using a direct request (key) for the object in memory (value).

There is no query language. By keeping indexes stored on distributed systems without worrying about where they are situated, the amount of data, or network slowdowns, it is possible to store large amounts of data on a distributed system.

Key-value databases are frequently regarded as the most basic type of NoSQL database. Due to the simplicity of this approach, key-value stores and databases are quick and easy to use.

However, there are several disadvantages to use a key-value database. Due to the fact that there is only one mechanism for querying the entire database (through a key), this can be a significant bottleneck. Not to mention the fact that not all data types can be queried.

A straightforward key-value database is both simple to create and extend. Its performance is typically great, and it may be modified to meet a business’s specific requirements. It is more likely that the system may slow down if you modify a key-value database and then add new applications to it.

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