Author Archives: Stanislav_Panteleev

✅ 1. Understand the Goals Requirement Description ⏱️ High availability Keep the application running with minimal disruption 💾 Data integrity Avoid data loss (use sync replication if needed) 🔄 Automatic switch Detect failure and switch to standby quickly 🔁 Failback … Continue reading →

The Saga pattern is a design pattern used to manage distributed transactions in microservices or distributed systems, where traditional ACID transactions are not feasible across services or databases. 🧠 What Problem Does It Solve? In distributed systems: A single business … Continue reading →

ACID compliance in distributed systems is a major challenge because you’re trying to guarantee strong consistency across multiple machines, each of which may fail independently, lose connectivity, or process operations at different speeds. 🧪 What is ACID? ACID stands for: … Continue reading →

🧠 Key Concept A Bloom filter is a bit array of fixed size, with multiple hash functions. You use it to: Insert: Map an item to a few bit positions and set those to 1. Query: Check if all the … Continue reading →

A Bloom filter helps optimize databases and storage systems by answering this question very efficiently: 🔍 “Does this item possibly exist?”(with a small chance of false positives, but zero false negatives) 🧠 What Is a Bloom Filter? A Bloom filter … Continue reading →

To implement full-text search (FTS) in SQL, you need to go beyond simple LIKE queries and use built-in text indexing and search functions that support: Tokenization (splitting into words) Ranking / relevance Stemming / stop words Boolean logic (AND, OR, … Continue reading →

✅ Short Answer: MVCC is a form of optimistic concurrency control, but not all optimistic locking is MVCC. 🧠 Detailed Comparison Feature MVCC Optimistic Locking (manual) Type System-level concurrency control Application or ORM-level concurrency control Uses versions? ✅ Yes — … Continue reading →

Multi-Version Concurrency Control (MVCC) is a concurrency control method used in databases to allow multiple users to read and write to the database without blocking each other. Instead of locking data for every read/write, MVCC keeps multiple versions of a … Continue reading →

🧠 1. Understand the Use Case Eventual consistency is useful when: High availability is critical. Temporary stale reads are acceptable (e.g., social media likes, shopping carts). You want to keep writing during network partitions. ⚙️ 2. Key Techniques for Eventual … Continue reading →

Eventual consistency is a consistency model used in distributed systems to ensure that, given enough time and no new updates, all replicas of a piece of data will converge to the same value. ✅ In Simple Terms: When you update … Continue reading →