System Design Interview

Two types of data exist in a typical chat system. The first is generic data, such as user profile, setting, user friends list. These data are stored in robust and reliable relational databases. Replication and sharding are common techniques to satisfy availability and scalability requirements. The second is unique to chat systems: chat history data. It is important to understand the read/ write pattern. •The amount of data is enormous for chat systems. A previous study [2] reveals that Facebook messenger and Whatsapp process 60 billion messages a day. •Only recent chats are accessed frequently. Users do not usually look up for old chats. •Although very recent chat history is viewed in most cases, users might use features that require random access of data, such as search, view your mentions, jump to specific messages, etc. These cases should be supported by the data access layer. •The read to write ratio is about 1: 1 for 1 on 1 chat apps. Selecting the correct storage system that supports all of our use cases is crucial. We recommend key-value stores for the following reasons: •Key-value stores allow easy horizontal scaling. •Key-value stores provide very low latency to access data. •Relational databases do not handle long tail [3] of data well. When the indexes grow large, random access is expensive. •Key-value stores are adopted by other proven reliable chat applications.