Key-Value Database in System Design

What is Key Value Database?

A key-value database is a type of non-relational 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, with each key being associated with a single value. The values can be simple data types such as strings or numbers, or they can be complex objects.

It is important to note that there is no connection between the values stored in a key-value database, and they are unrelated to one another. Additionally, the keys must be unique to ensure that there is no ambiguity when searching for a specific value in the database.

Key value database example

In a key-value database, data is organized into tables with rows and columns, similar to a standard relational database. However, the developer can specify many attributes of the data in advance, which can allow for optimizations such as data compression, data aggregation, and faster data access.

Key-value databases are generally more flexible and offer faster read and write performance compared to relational databases, which may require more complex aggregations to retrieve data. Instead, a key-value database simply looks up the value associated with a specific key, making it a more efficient option for certain types of data storage and retrieval.

Key-value database operations

A key-value store is a type of database that allows users to store, access, and update data using simple commands such as "get," "put," and "delete." This simplicity makes key-value stores fast, easy to use, portable, and flexible. They are also highly partitionable and can scale horizontally, which means they can handle large amounts of data and traffic without slowing down.

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

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

Overall, key-value stores are a useful tool for storing and managing data in a fast and efficient way.

Key-value database operations

Properties of Key-Value Database

Key-value databases are used in applications where a single type of item can be searched for based on a single property, and they offer significant speed and scalability benefits compared to traditional databases. Key-value storage systems typically aim to achieve the following properties:

Consistency: Most key-value databases claim to be eventually consistent, which means that data updates must be propagated to all nodes in the system. This ensures that all copies of the data are consistent, and that retrieving a value for a particular key will always return the same result.

Throughput: Key-value databases focus on maximizing the number of transactions that can be performed in a given unit of time, known as throughput.

Scalability: A key-value database system is considered scalable if it can distribute data and read/write operations across multiple servers, which can improve performance.

Availability: The availability feature ensures that readers and writers can always access the data, and that it is available to users at all times.

Partition Tolerance: Data is typically stored in multiple locations to ensure that the system can handle failures of individual servers and continue functioning as a whole.

When to use key-value database?

There are several situations in which it may be a good idea to use a key-value database to store data. These databases are well-suited for processing a constant stream of read/write operations with low latency on large-scale data, and they have built-in redundancy that can handle lost storage or data without issues. Some specific scenarios where a key-value database might be used include:

Session management: A key-value database can be used to manage and store session attributes in online applications on a large scale. For example, it might be used to manage the sessions of individual players in a multiplayer online game.

In-memory data caching: A key-value database can be used as an effective cache mechanism for frequently accessed but rarely updated data, helping to accelerate application responses.

User preference storage and personalization: A key-value database can be used to provide product recommendations and store personalized lists of items for individual customers. This is often used in e-commerce applications.

Implementing blockchain-based solutions: Key-value databases are often used when implementing blockchain-based ideas. In this case, the key is typically a hash value and the value is the corresponding block entity.

Real-time random data access: Key-value databases offer fast in-memory access, making them useful in situations where an application needs to handle many small continuous reads and writes.

Storing basic information: A key-value database can be used to store basic data based on key-value pairs. For example, it might be used to store web page URLs as the keys and the web pages themselves as the values.

Content delivery networks: A key-value database can be used for storing and serving large web objects (such as videos, images, and audio) in a high availability environment, such as a content delivery network.

Different types of key-value databases

There are several different implementations of key-value databases available on the market, each offering different features and capabilities. Some examples include:

Aerospike: Aerospike is a leading provider of real-time NoSQL data solutions that offer low latency and predictable performance at any scale, with industry-leading uptime.

Apache Cassandra: Apache Cassandra is an open-source NoSQL distributed database designed for scalability and high availability without compromising on performance. It was initially developed by Facebook and released as open-source in 2008. Cassandra uses complex data structure building blocks to generate multi-dimensional hashes that represent data, with values consisting of key-value pairs.

Amazon DynamoDB: Amazon DynamoDB is a fully managed, multi-region, multi-master, persistent key-value and document database with single-digit millisecond performance. It offers built-in security, backup and restore, and in-memory caching for internet-scale applications.

Berkeley DB: Berkeley DB is a family of embedded key-value database libraries that provide scalable, high-performance data management services to applications. Records in Berkeley DB consist of key-value pairs, and three different access methods (B+tree, hashing, and fixed-or-variable-length records) are available for operating on keys.

Memcached: Memcached is an open-source, in-memory data caching system that speeds up webpages by caching data and objects in RAM to reduce the need to access external data sources. It is available for free.

Riak: Riak is a key-value database inspired by Dynamo, written primarily in Erlang. Data in Riak is organized into pairs of keys and values stored in a "bucket," which serves as a namespace and allows the same key to appear in multiple buckets. Riak has a native interface and an HTTP API that allows users to manipulate data using GET, PUT, POST, and DELETE methods.

Redis: Redis is a key-value database that supports a variety of data structures, including strings, lists, sets, sorted sets, and hashes. It only supports insert, update, delete, and lookup operations, and data is kept in RAM by Redis servers with the option to write to disk at customisable intervals for backup and system shutdown.

Key-value store Vs Cache

A key-value database can be used as a cache to provide real-time information by quickly returning a value for a specific key. It can store a pool of frequently accessed data in order to improve performance for future requests. However, 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 in conjunction with a database to increase read performance.
  • Caches are not designed to enhance write or update performance, whereas key-value databases can be very effective for these operations.
  • While key-value databases can be resilient to server failure, caches are typically stored in RAM and do not offer transactional guarantees if the server crashes.

Overall, a key-value database can be a useful tool for storing and accessing data in real-time, while a cache can be used to improve the performance of read operations in conjunction with a traditional database.

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