Caching Layers in NewSQL Databases

Introduction

Caching is a critical aspect of database performance optimization, especially in NewSQL databases which are designed to handle high transaction volumes while maintaining the consistency of relational databases. This lesson will cover the fundamentals of caching layers, their importance, and best practices for implementation.

What is Caching?

Caching is the process of storing copies of files or data in a temporary storage location (cache) so that future requests for that data can be served faster. By storing frequently accessed data closer to the application layer, caching reduces latency and improves application performance.

Caching Layers

Caching layers can be classified into different types based on their placement within the architecture:

• Application-level Cache
• Database Query Cache
• Distributed Cache
• Content Delivery Network (CDN)

Application-level Cache

This cache resides within the application itself and is used to store frequently accessed data or computed results.

const redis = require('redis');
const client = redis.createClient();

function getData(key) {
    return new Promise((resolve, reject) => {
        client.get(key, (err, data) => {
            if (err) return reject(err);
            if (data) return resolve(JSON.parse(data));

            // Fetch from database if not cached
            const result = fetchFromDatabase(key);
            client.setex(key, 3600, JSON.stringify(result)); // Cache for 1 hour
            resolve(result);
        });
    });
}

Database Query Cache

Many NewSQL databases provide built-in query caching mechanisms that store the results of frequently executed queries to speed up response times.

Distributed Cache

Distributed caches like Memcached or Redis can be used to store data across multiple nodes, providing a scalable solution for cache storage.

Content Delivery Network (CDN)

CDNs are used primarily for caching static content, such as images or scripts, at edge locations closer to users, reducing load times.

Best Practices

Implementing caching layers effectively requires careful consideration. Here are some best practices:

• Identify data that benefits from caching, such as frequently accessed or computationally expensive results.
• Set appropriate expiration times for cached data to ensure data freshness.
• Use versioning or cache busting techniques when the underlying data changes.
• Monitor and analyze cache performance to optimize cache hits and misses.
• Implement fallback mechanisms to retrieve data directly from the database when cache misses occur.

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