(Part-1) Understanding Redis Design and Consistency Models in Distributed Systems скачать в хорошем качестве

(Part-1) Understanding Redis Design and Consistency Models in Distributed Systems

If you need any assistance with Faang interviews, or if you would like to join my live sessions on Leetcode prep, contact me via whatsapp at (+91)8368260085 Outline of Problems Discussed: Scalability Issues with Local Hash Maps: Local hash maps are not scalable for distributed services. 1 Caching vs. Persistent Databases: Redis as an in-memory key-value store should be treated as a cache, not a persistent database. 2 Access Time Complexity: Accessing data from cache (nanoseconds) vs. hard drive (milliseconds). 3 Write-Heavy vs. Read-Heavy Systems: Differences in caching needs for write-heavy and read-heavy systems. 4 Consistency in Distributed Systems: Challenges in maintaining consistency across multiple nodes. 5 CAP Theorem: Trade-offs between Consistency, Availability, and Partition Tolerance. 6 Hashing and Consistent Hashing: Issues with traditional hashing and benefits of consistent hashing. 7 Data Replication: Importance of replicating data across multiple nodes to avoid single points of failure. 8 Quorum-Based Consistency: Using read and write quorums to achieve strong consistency.