Technical Blog

  Introduction In former times , relational databases grew increasingly dominant. It delivers rich indexes to make any query efficient. Table joins, which are used for operations that pull together separate records into one. And transactions, which meant a combination of reads and especially writes across the database. But, they need to happen together. Strict guarantees were engineered in to prevent surprises. Relational databases designed around the assumption of running on a single machine lacks something that became essential with the advent of the internet. They were painfully difficult to scale out. The volume of data that can be created by millions or billions of networked humans and devices is more than any single server can handle. When the workload grows so heavy that no single computer can bear the the load. When the most expensive hardware on the market will be brought to its knees by the weight of an application. The only path is to move forward from a single data...

     Introduction We might be so strong and familiar with things while learning. But when we want to put that in practice, we just need a quick reference for confirmation. Been there ? This blog will be a quick brush up on few concepts about MongoDB basics and cluster administration.  Overview In Mongo, the database is referred as  namespace , which stores  collections (tables). The collections store individual record called  documents . We can establish security at various levels. We can either authorize at database level or collection level, but document level authorization is not supported. Schema - Provides list of fields, datatype, summary for range of values for each fields. Can be defined using JSON schema. For detailed overview on schema check  MongoDB schemas . Supported datatypes are String, Integer, Boolean, Double, Min/Max keys, Arrays, Timestamp, Object, Null, Symbol, Date, Object ID, Binary data, Code and Regular expressions. Frequen...