Suggestions
Balraj Singh
Engineer @ Meta(Facebook) - ex-N26 - Mobile Specialist - iOS, Swift,Server Driven UI, CI/ CD, Testing - Blogger
Balraj Singh is an energetic software engineer with over 10 years of experience specializing in developing simple and anti-fragile software solutions tailored for high-volume businesses. He has a proven track record of enhancing Mobile App's stability and responsiveness through the integration of innovative patterns and coding practices.
Balraj holds a Bachelor of Technology (BTech) degree in Information Technology from JSS Academy of Technical Education. His educational foundation has equipped him with comprehensive knowledge and skills to excel in the technology industry.
Throughout his career journey, Balraj has held notable positions at renowned organizations, including Facebook, where he currently serves as a Software Engineer. He has previously worked as a Senior iOS Engineer at N26, Senior Software Engineer at Halodoc ID, Senior Software Development Engineer at Hike Messenger, and Software Development Engineer III at Ola under ANI Technologies Pvt Ltd.
Prior to these roles, Balraj honed his expertise as a Senior Software Engineer at TechJini Inc., Windows 8/Windows Phone Application Developer at Posh Technologies Inc., and Software Developer at MAQ Software. His diverse experience across various tech companies has contributed to his proficiency in software development and engineering.
Aside from his professional engagements, Balraj is also a prolific writer, having authored 10 insightful blogs on Medium focusing on general programming skills and best practices. His dedication to sharing knowledge and expertise underscores his passion for continuous learning and growth in the tech field.
Highlights
𝗛𝗼𝘄 Airbnb 𝘀𝗰𝗮𝗹𝗲𝗱 𝘁𝗵𝗲𝗶𝗿 𝗣𝗼𝘀𝘁𝗴𝗿𝗲𝘀 𝗱𝗮𝘁𝗮𝗯𝗮𝘀𝗲 𝘁𝗼 𝗶𝗻𝗳𝗶𝗻𝗶𝘁𝗲 𝘀𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆
Airbnb scaled their Postgres database to handle the increasing demands of their platform by employing several strategies:
-
Horizontal Scaling: In the first stage Airbnb used sharding to horizontally partition their database. This involved breaking the database into smaller, more manageable pieces called shards. Each shard contains a subset of the data and operates independently. By distributing data across multiple servers, Airbnb improved scalability and performance.
-
Replication: They implemented master-slave replication to improve fault tolerance and redundancy. In this setup, the master database handles write operations while one or more slave databases replicate the data from the master.
-
Caching: Airbnb utilized caching mechanisms to reduce database load and improve query performance. They implemented caching at various levels, including application-level caching using tools like Memcached and Redis, as well as content delivery network (CDN) caching for static content.
-
Optimized Indexing: Efficient indexing is crucial for fast data retrieval. Airbnb carefully analyzed query patterns and optimized indexing strategies to ensure that queries executed efficiently, minimizing the need for full table scans and improving overall performance.
-
Query Optimization: They focused on optimizing database queries by using query analyzers and profilers to identify bottlenecks and inefficiencies. By fine-tuning SQL queries and optimizing database schema design, Airbnb was able to improve query performance and reduce resource consumption.
-
Database Monitoring and Management: Continuous monitoring of database performance is essential for identifying issues and maintaining optimal performance.
Airbnb implemented robust monitoring tools to track database metrics, detect anomalies, and troubleshoot performance issues in real time.
#Airbnb #Database
