#Redis

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#Redis Reel by @thatcodergirlie (verified account) - Comment "blog" & I'll share the blog link with you in your DM 🤝🏻 (Make sure to follow else automation won't work) Topic: Redis (database that answ
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@thatcodergirlie
Comment “blog” & I’ll share the blog link with you in your DM 🤝🏻 (Make sure to follow else automation won’t work) Topic: Redis (database that answers millions of request in microseconds that too with a single thread) Save for your future interviews 📩 #dsa #systemdesign #tech #coding #codinglife [dsa, system design, redis, tech]
#Redis Reel by @qubitship - Redis is a super-fast in-memory database that stores data in RAM instead of disk. In a client-server-database system, Redis is used to cache and quick
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@qubitship
Redis is a super-fast in-memory database that stores data in RAM instead of disk. In a client-server-database system, Redis is used to cache and quickly retrieve data, improving performance and reducing load on the main database. Perfect for real-time apps, caching, and session storage. #education #redis #coding #programming #computerscience
#Redis Reel by @codewithupasana - I deleted entire redis cluster 🥲 So, I needed to perform one task, where I had to bring up all the instances of our redis cluster. Everything was g
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@codewithupasana
I deleted entire redis cluster 🥲 So, I needed to perform one task, where I had to bring up all the instances of our redis cluster. Everything was going fine until I ran that one wrong command. I had to delete one instance and recreate it, instead I deleted the entire instace group which eventually deleted all the instances of our redis cluster. What’s next? Complete quos🥲 #redis #outage #flipkart #delete #engineer
#Redis Reel by @arjay_the_dev (verified account) - What is Redis and how is it so fast?? Redis is your best friend for caching and speed. #coding #programming #databases #redis
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@arjay_the_dev
What is Redis and how is it so fast?? Redis is your best friend for caching and speed. #coding #programming #databases #redis
#Redis Reel by @tom.developer (verified account) - Redis is the newest addition to the tech stack of one of my projects as we begin to handle more users! 💻 Redis is an in-memory data store. Data is s
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@tom.developer
Redis is the newest addition to the tech stack of one of my projects as we begin to handle more users! 💻 Redis is an in-memory data store. Data is stored as a key, followed by a value which can be one of many different data structures. This makes it easy to store data within Redis exactly how it’s being used in your application, instead of having to conform to a specific data structure. 👍 #softwareengineer #softwaredeveloper #programming #coding #developer #programmer #software #computerscience #javascript #coder #webdeveloper #codinglife #python #code #java #softwaredevelopment #webdevelopment #programmers #technology #html #softwareengineering #tech #programminglife #css #webdesign #programmingmemes #developers #engineering #development #programmerlife
#Redis Reel by @sjain.codes - 1️⃣ In-Memory Data Store (Biggest Reason) Redis stores data entirely in RAM, not on disk. 👉 No disk seek time 👉 No I/O wait 👉 No blocking reads
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@sjain.codes
1️⃣ In-Memory Data Store (Biggest Reason) Redis stores data entirely in RAM, not on disk. 👉 No disk seek time 👉 No I/O wait 👉 No blocking reads Accessing RAM takes nanoseconds, while disk access takes milliseconds. So operations like: • GET • SET • INCR • HSET are extremely fast. ⸻ 2️⃣ Single Thread = No Locking Overhead Traditional databases: • Multiple threads • Shared memory • Locks & synchronization • Context switching Problems: • Mutex locks • Race conditions • CPU context switching cost Redis avoids all of this. ✅ Only one thread executes commands ✅ No locks ✅ No thread contention So every request executes deterministically and quickly. Key Insight: Redis trades parallelism for simplicity and predictability. ⸻ 3️⃣ Event Loop + Non-Blocking I/O Redis uses an event-driven architecture similar to Node.js. It relies on OS mechanisms like: • epoll (Linux) • kqueue (Mac) • select/poll Flow: 1. Thousands of clients send requests. 2. Requests are queued in socket buffers. 3. Event loop detects ready connections. 4. Redis processes commands sequentially. Since network I/O is non-blocking, Redis never waits for clients. 👉 One thread can handle tens of thousands of connections simultaneously. ⸻ 4️⃣ Extremely Fast Data Structures Redis operations are optimized: • Hash tables → O(1) • Lists → optimized linked structures • Sorted Sets → skip lists • Bitmaps & HyperLogLog Most commands execute in constant time. ⸻ 5️⃣ Pipelining (Hidden Performance Booster) Clients can send multiple commands without waiting for responses. This reduces network round trips massively. ⸻ 6️⃣ Modern Redis Uses Threads (Important Detail) Redis is not fully single-threaded anymore. Execution is single-threaded, BUT: ✅ Networking I/O uses multiple threads ✅ Background threads handle: • Persistence (RDB/AOF) • Replication • Lazy deletion So the main thread focuses only on fast command execution. #systemdesigninterview #coding #code #google #ai
#Redis Reel by @pirknn (verified account) - Comment "REDIS" to get links! 🚀 Want to really understand what Redis is and how it makes your backend super fast? This mini roadmap takes you from t
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@pirknn
Comment "REDIS" to get links! 🚀 Want to really understand what Redis is and how it makes your backend super fast? This mini roadmap takes you from total beginner to using Redis as a cache, session store and even primary database in real projects. 🎓 What is Redis Start here if you have never used Redis before. In a few minutes you will understand what an in memory data store is, how Redis works, and why it is different from traditional SQL and NoSQL databases. Perfect for building the big picture before you touch any code. 📘 Redis Crash Course Next, go deeper into real commands and data structures. You will see how to use strings, lists, sets and hashes, and how to connect Redis from your backend code. This helps you cache expensive database queries, speed up APIs and reduce response time for real users. 💻 Redis DB Guide Finally, learn the what, why and how of using Redis as a serious part of your architecture. You will see patterns for using Redis as a cache layer, message broker and primary database, and understand when you should or should not rely on it in production system design. 💡 With these Redis resources you will learn how to: Design fast and scalable backend architectures with Redis Cache database queries to avoid slow responses Handle sessions, rate limiting and queues in real projects Speak confidently about Redis in system design interviews If you are serious about backend engineering, high performance APIs or system design, learning Redis is a huge advantage. 📌 Save this post so you do not lose the roadmap. 💬 Comment "REDIS" and I will send you all the links. 👉 Follow for more content on Redis, caching, backend engineering and system design.
#Redis Reel by @coding.kitty - Redis explained by cats. Follow for more. #cat #redis #software #developer #coding
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@coding.kitty
Redis explained by cats. Follow for more. #cat #redis #software #developer #coding
#Redis Reel by @thatcodergirlie (verified account) - Comment "blog" & I'll share the blog link & notes with you in your DM 🤝🏻 (Make sure to follow else automation won't work) Problem: Persistence in
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@thatcodergirlie
Comment “blog” & I’ll share the blog link & notes with you in your DM 🤝🏻 (Make sure to follow else automation won’t work) Problem: Persistence in Redis (your e-commerce website stores data in redis & suddenly, server restarts, but your data is not lost) Save for your future interviews 📩 #dsa #systemdesign #tech #coding #codinglife [dsa, system design, redis, tech, persistence]
#Redis Reel by @mission_compile - It sounds impossible… but it's actually smart engineering. Comment "blog" for detailed blog. ⸻ ➡️ 1️⃣ No Thread Switching Overhead Redis runs on a s
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@mission_compile
It sounds impossible… but it’s actually smart engineering. Comment "blog" for detailed blog. ⸻ ➡️ 1️⃣ No Thread Switching Overhead Redis runs on a single event loop, no context switching between threads. Example: One cashier serving customers quickly instead of 5 cashiers fighting over the same drawer. ⸻ ➡️ 2️⃣ Everything Is In-Memory Redis stores data in RAM, not disk. Example: Reading from RAM takes microseconds vs milliseconds from disk. ⸻ ➡️ 3️⃣ Non-Blocking I/O (Event Loop Model) Uses an event-driven model (epoll/kqueue). Example: While waiting for one client’s network response, it serves others instead of waiting idle. ⸻ ➡️ 4️⃣ Simple Data Structures Optimized internal structures (hash tables, skip lists). Example: Fetching a user session is just a quick hash lookup - no heavy joins. ⸻ ➡️ 5️⃣ Pipelining Clients can send multiple commands at once without waiting for each response. Example: Instead of 10 back-and-forth trips, send 10 commands in one go. ⸻ ➡️ 6️⃣ Horizontal Scaling Redis scales using replication and clustering. Example: 1 instance handles 100K ops → 10 shards handle 1M+ ops. ⸻ ➡️ 7️⃣ Multi-Threaded I/O (Modern Redis) Newer versions use threads for network I/O while keeping command execution single-threaded. (redis architecture explained, redis single threaded performance, how redis handles high throughput, redis event loop model, in memory database performance, redis pipelining and clustering, backend performance optimization) #Redis #BackendEngineering #SystemDesign #ScalableSystems #DistributedSystems
#Redis Reel by @neatroots - Ever wondered how BookMyShow handles seat booking without chaos? 🎟️ Here's the real system design logic behind it 👇 🔹 1️⃣ User Selects Seats When
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@neatroots
Ever wondered how BookMyShow handles seat booking without chaos? 🎟️ Here’s the real system design logic behind it 👇 🔹 1️⃣ User Selects Seats When you select seats: • The request goes to Seat Availability Service • Seats are checked in real-time cache (Redis) for speed ⸻ 🔹 2️⃣ Seat Locking (MOST IMPORTANT) To avoid double booking: • Selected seats are LOCKED temporarily • Lock duration: 5–10 minutes • Status changes from: • AVAILABLE → LOCKED ⚠️ Other users cannot see or select locked seats ⸻ 🔹 3️⃣ Distributed Lock Mechanism Behind the scenes: • Redis / Zookeeper / DB Row Lock • Ensures only ONE user can lock a seat • Prevents race conditions in peak traffic ⸻ 🔹 4️⃣ Payment Flow • User is redirected to payment gateway • Two possible outcomes: ✅ Payment Success • Seat status → CONFIRMED • Booking ID generated • Notification sent ❌ Payment Failed / Timeout • Lock expires automatically • Seats become AVAILABLE again ⸻ 🔹 5️⃣ Why Cache is Critical • Millions of reads per minute • DB alone would crash • Redis Cache = fast seat availability • DB used only for final confirmation ⸻ 🔹 6️⃣ High-Level Architecture • API Gateway • Seat Service • Booking Service • Payment Service • Cache (Redis) • Database (Transactional) ⸻ 🚀 Final Thought BookMyShow doesn’t just sell tickets… It masters concurrency, locking, and scalability 💡 #systemdesign #bookmyshow #softwarearchitecture #backendengineering #scalablesystems hightraffic redis distributedSystems techreels codingreels developerlife interviewprep faang backenddeveloper engineeringexplained softwareengineer softwaredevelopment softwareengineering

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