Explain the features of Amazon MemoryDB for Redis

In this recipe, we will learn about Amazon MemoryDB for Redis. We will also learn about the features of Amazon MemoryDB for Redis.

Recipe Objective - Explain the features of Amazon MemoryDB for Redis?

The Amazon Managed Grafana is a widely used service and is defined as a fully managed service for ultra-fast performance, using a Redis-compatible, durable, in-memory database service. MemoryDB for Redis aims to combine the functions of a cache and a database into a single component that offers microsecond read latency and data durability. Build applications quickly with Redis, the "Most Loved" database on Stack Overflow for the past five years. Process over 13 trillion requests per day and over 160 million requests per second to access data at lightning speed. In-memory storage with a Multi-AZ transactional log for fast database recovery and restart ensures data durability. Scale from a few gigabytes to over a hundred terabytes of storage per cluster to meet users' application requirements. Amazon MemoryDB has a throughput of up to 1.3 GB/s read and 100 MB/s write per node and can handle up to 390K read and 100K write requests per second (based on internal Amazon testing on read-only and write-only workloads). Latency is measured in microseconds for reads and single-digit milliseconds for writes. Scaling in both vertical and horizontal directions. Data sharding and read replicas are possible. On the primary node, there is a lot of consistency, and on the replica nodes, there are a lot of consistency reads. MemoryDB's consistency model is similar to ElastiCache for Redis. MemoryDB, on the other hand, does not lose data during failovers, allowing clients to read their writes from primary nodes even if nodes fail. Only data from the multi-AZ transaction log that has been successfully persisted is visible. Replica nodes eventually become consistent.

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Benefits of Amazon MemoryDB for Redis

  • Lossless failover is supported by MemoryDB. When a primary node fails, MemoryDB will failover automatically and promote one of the replicas to serve as the new primary, redirecting write traffic to it. MemoryDB also employs a distributed transactional log to ensure that data on replicas remains current, even in the event of a primary node failure. For unplanned outages, failover takes less than 10 seconds, and for planned outages, it takes less than 200 milliseconds and thus it supports lossless failover. MemoryDB stores your entire data set in memory and provides data durability through a distributed multi-AZ transactional log and thus offers data durability. During the maintenance windows you specify, MemoryDB automatically patches your cluster. MemoryDB uses service updates for some updates, which you can apply immediately or schedule for a later maintenance window and thus it offers a managed service.

System Requirements

  • Any Operating System(Mac, Windows, Linux)

This recipe explains Amazon MemoryDB for Redis and the Features of Amazon MemoryDB for Redis.

Features of Amazon MemoryDB for Redis

    • It provides Redis compatibility

Redis is a key-value data store that runs in memory and is open source. Redis allows developers to achieve sub-millisecond response times, allowing millions of requests per second for real-time applications in industries such as gaming, ad tech, financial services, healthcare, and the Internet of Things. For the fifth year in a row, Redis was named Stack Overflow's "most loved database" in 2021. To create agile and versatile applications, Redis provides flexible APIs, commands, and data structures such as streams, sets, and lists. MemoryDB is backwards compatible with open source Redis, and it supports the same set of Redis data types, parameters, and commands. This means that you can use the same code, applications, drivers, and tools that you use with Redis to quickly build applications with MemoryDB Service.

    • It provides ultra-fast performance

MemoryDB reads and writes users' entire dataset in memory, resulting in microsecond read latency and single-digit millisecond write latency, as well as high throughput. It can handle over 13 trillion requests per day and 160 million requests per second at its peak. As these applications can involve interactions with many service components per user interaction or API call, developers working with microservices architectures require ultra-high performance. MemoryDB allows users to deliver real-time performance to end users with extremely low latency.

    • It provides the durability of Multi-AZ

MemoryDB uses a distributed transactional log to provide data durability, consistency, and recoverability in addition to storing your entire data set in memory. MemoryDB distributes data across multiple AZs, allowing for quick database recovery and restart. Instead of managing a cache for speed and an additional relational or nonrelational database for reliability, you can use MemoryDB as a single, primary database service for workloads requiring low latency and high throughput.

    • It provides scalability

Users can scale their MemoryDB cluster horizontally by adding or removing nodes, or vertically by switching to larger or smaller node types to meet changing application demands. MemoryDB supports sharding for write scaling and replicas for reading scaling. During resizing operations, the users' cluster remains online and supports read and write operations.

    • It provides security in networking

MemoryDB is hosted in an Amazon Virtual Private Cloud (VPC), which allows users to isolate users databases in its virtual network and connect to their on-premises IT infrastructure using industry-standard, encrypted IPsec VPNs. Users can also configure firewall settings and control network access to their database instances using MemoryDB's VPC configuration.

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I am the Director of Data Analytics with over 10+ years of IT experience. I have a background in SQL, Python, and Big Data working with Accenture, IBM, and Infosys. I am looking to enhance my skills... Read More

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