Introduction to Key-Value Database

A key-value database is a NoSQL database that stores data in the form of key-value pairs. These key-value pairs are similar to the way data is stored in a map or dictionary, where each key is associated with a single value. Here key serves as a primary key and values can be simple data types like strings or numbers, or complex data structures like JSON. So there are two important points to keep in mind:

• There is no connection between the values stored in a key-value database.
• Keys are unique to ensure that there is no ambiguity when searching for a specific value.
• Key-value databases provide faster read and write performance compared to relational databases, which may require complex aggregations to retrieve data.
• There are several implementations of key-value databases available. Each one of them has some unique features and capabilities. Here are some examples: Aerospike, Apache Cassandra, Amazon DynamoDB, Berkeley DB, Memcached, Riak, Redis, etc.

Key-value database operations

A key-value database helps users to store, access, and update data using simple commands like get, put, and delete. This simplicity makes key-value stores fast, easy to use, portable, and flexible. They are also partitionable and can scale horizontally i.e. they can handle large data and traffic without slowing down.

Some common operations that can be performed on a key-value databases:

• get(key): Retrieve the value associated with a key.
• put(key, value): Insert a value into the database associated with a key.
• delete(key): Remove the value associated with a key.
• update(key, value): Update the value associated with a key.

Some key-value databases also provide some of these operations:

• Retrieving a range of keys or all the keys in the database.
• Retrieving key-value pairs within a specified range of keys.
• Some operations can execute atomically without interference from concurrent operations.
• Performing multiple put, get, or delete operations together as a single atomic operation.
• Associating additional keys with specific values. These secondary keys can be used for efficient retrieval of data based on criteria other than the primary key.
• Setting an expiration time for a key-value pair. Once the TTL expires, the key-value pair is automatically deleted. This can be useful for implementing cache invalidation mechanisms.

Characteristics of key-value databases

• Key-value databases use replication to maintain multiple copies of data across different nodes. This ensures that users have access to data even if some nodes become unavailable.
• They are designed to be partition-tolerant i.e. they can continue to operate even in the presence of network partitions or communication failures.
• Most key-value databases prioritize availability and partition tolerance over strong consistency. So after a write operation, it may take some time for the data to become consistent across all nodes.
• They can handle large data by distributing read and write across multiple servers.
• Key-value databases use in-memory storage and optimized data structures. So they are highly optimized for fast data retrieval based on the key, which can provide low latency and high throughput.
• Each key-value pair is independent and the structure of the values can vary across different records. So it does not require a predefined schema or data model.
• Key-value databases lack complex querying capabilities compared to relational databases. The idea is simple: They are designed for simple key-based lookups for retrieving values. But some key-value databases extend their query capability by providing features like secondary indexes or range queries.

Use cases of key-value database

• We can use it to store session attributes in online applications. For example, it can manage the sessions of individual players in a multiplayer online game.
• We can use it as an effective cache mechanism for frequently accessed but rarely updated data.
• We can use it to provide product recommendations by storing personalized items for customers.
• Key-value databases offer fast in-memory access. This makes them useful in situations where an application needs to handle many small continuous reads and writes.
• We can easily store some basic data based on key-value pairs in key-value database. For example, we can use it to store URLs as keys and web pages as values.
• We can use it to store large web objects (videos, images) in a system like content delivery network.

Key-value store Vs Cache

As we have seen above, a key-value database can be used as a cache to store frequently accessed data to improve performance. But there are some differences between a cache and a key-value store:

• While a key-value database can be used to persist data, caches are used to increase read performance.
• Caches are not designed to enhance write performance, whereas key-value databases can be very effective for the write operations.
• While key-value databases are designed to be resilient to server failure, caches are typically stored in RAM and do not offer transactional guarantees if the server crashes.

Are key-value databases similar to tables in RDBMS?

Key-value databases and tables in RDBMS have some similarities, but they are different in terms of their data models and structures. Here are some of the key differences:

• In an RDBMS, data is organized into structured tables of rows and columns. It requires a predefined schema that specifies the structure of tables like column names, data types, relationships, etc. But key-value databases do not have a fixed schema. Here each key-value pair can have a different structure.
• RDBMS typically use SQL, which allows complex queries like joins, aggregations, and filtering across multiple tables. On the other side, key-value databases often provide a simpler interface with basic operations like get, put, and delete based on the key.
• RDBMS can establish relationships between tables using primary and foreign keys. But key-value databases do not have built-in mechanisms for managing relationships between data. So it is up to the application developer to handle any relationships.
• RDBMS provide ACID properties and ensure data consistency and integrity. On the other side, key-value databases often prioritize availability and partition tolerance over strong consistency.

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