Database Sharding Crash Course (with Postgres examples) Database sharding is process of segmenting the data into partitions that are spread on multiple database instances to speed up queries and scale the system. What is sharding? sharing key / partition key Consistent Hashing Horizontal partitioning vs Sharding Example Pros and cons What is Sharding? 1:30 Consistent Hashing 4:50 Horizontal partitioning vs Sharding 7:36 Example 8:45 Spin up Docker Postgres Shards 10:02 Write to the shard 17:25 Read from the Shard 39:20 Pros & Cons 51:10 Cards Postgres pgadmin Docker 8:54 Postgres Javascript 18:18 URL vs Query param 22:30 CORS 29:30 sql injection 42:40 Source Code https://github.com/hnasr/javascript_playground/tree/master/sharding Docker commands (including pgadmin) https://github.com/hnasr/javascript_playground/blob/master/sharding/shards/commands.txt Dockerfile & init.sql https://github.com/hnasr/javascript_playground/tree/master/sharding/shards Horizontal partitioning vs Sharding HP same database instance so you can still join sharding across instances (different server) Pros Extreme scale rdbms Optimal and Smaller index size Cons Transactions across shards problem Rollbacks Schema changes Complex client (aware of the shard) Joins Has to be something you know in the query Example URL shortener create table CREATE TABLE public.test1 ( id serial NOT NULL primary key, url text, url_id character(5) ) Spin up 3 instances p1 P2 P3 post get

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