Redis hashes are data structures that store mappings of string fields to string values. They are useful for representing objects, such as user profiles, and allow efficient storage and retrieval of field-value pairs

Pub/sub (publish/subscribe) in Redis is a messaging paradigm where publishers send messages to channels, and subscribers receive messages from those channels. It's commonly used for real-time messaging applications.

Redis can be easily run in Docker containers using official Redis images. It supports containerized deployments for scalability, portability, and easy environment setup.

Redis is single-threaded, which simplifies the architecture by avoiding concurrency issues. It handles multiple client connections through multiplexing, ensuring thread safety without the complexities of multi-threading.​

Redis is not fully ACID-compliant like traditional databases. However, it offers atomicity for individual operations and transactions, supporting data integrity to a reasonable extent.

Yes, Redis is ideal for real-time analytics due to its in-memory architecture, low latency, and data structures like sorted sets and hyperloglogs, which are great for fast data processing.

Key eviction in Redis occurs when the memory limit is reached. Redis can remove keys based on policies like volatile-lru (least recently used among keys with an expiry set) or allkeys-lru (least recently used among all keys).

While both are in-memory data stores, Redis supports more complex data types, persistence, replication, and pub/sub, whereas Memcached focuses purely on caching with simpler key-value pairs.

Redis provides commands like MONITOR, SLOWLOG, and INFO to monitor and debug performance. External tools like Redis Insight and Prometheus can also be integrated for detailed analysis.

Redis offers two persistence options:

• RDB (Redis Database Backup): Periodic snapshots of the dataset.
• AOF (Append Only File): Logs every write operation received by the server. Combining both provides a balance between performance and durability.

Redis is an in-memory data structure store used as a NoSQL database, cache, and message broker. It supports various data structures such as strings, hashes, lists, sets, and sorted sets, offering high performance for both reads and writes.​

 RDB creates snapshots of the dataset at specified intervals, offering faster restarts but potential data loss. AOF logs every write operation, providing better durability at the cost of larger file sizes and slower restarts.

Redis can be used as a distributed cache by deploying it in a clustered setup. This ensures data is cached across multiple nodes, providing scalability and fault tolerance.

Lua scripting in Redis allows developers to execute custom scripts atomically on the server side, reducing the number of round trips between client and server and improving performance.

Enabling persistence in Redis can impact performance due to disk I/O operations. The choice between RDB and AOF, or a combination, should be based on the application's durability requirements and performance considerations.

The Redis Stream data type enables managing time-series data, logs, and messaging queues. It supports features like consumer groups, making it suitable for distributed systems.

Redis is an in-memory store, providing faster data access compared to traditional disk-based databases like MySQL. While MySQL supports complex queries and joins, Redis excels in scenarios requiring quick data retrieval and simple operations.

 Redis Sentinel provides high availability for Redis. It monitors master and replica instances, performs automatic failover if the master goes down, and notifies the system of topology changes.

Redis transactions allow the execution of a group of commands in a single atomic step using commands like MULTI, EXEC, DISCARD, and WATCH. This ensures that either all commands are executed or none, maintaining data integrity.

Redis uses an allocator like jemalloc or libc and provides configuration settings to control memory usage. Administrators can set memory limits and eviction policies to manage memory effectively.

Redis clustering allows data to be automatically partitioned across multiple nodes, enabling horizontal scalability and high availability. It supports automatic failover and rebalancing of data.

Redis offers features like password authentication, SSL/TLS encryption, and access control lists (ACLs) to secure data and restrict access.

All commands in Redis are atomic by default due to its single-threaded nature. For batch atomicity, Redis provides transactions and Lua scripting.

A Redis pipeline allows clients to send multiple commands without waiting for individual responses, greatly reducing network latency and improving performance for batch operations.

Redis replication follows a master-slave architecture where the master handles writes and replicates data to one or more slave instances for redundancy and read scalability.