Why are SQL databases not scalable?

The main reason relational databases cannot scale horizontally is due to the flexibility of the query syntax. SQL allows you to add all sorts of conditions and filters on your data such that it’s impossible for the database system to know which pieces of your data will be fetched until your query is executed.

Does join affect query performance?

Join order in SQL2008R2 server does unquestionably affect query performance, particularly in queries where there are a large number of table joins with where clauses applied against multiple tables. Although the join order is changed in optimisation, the optimiser does’t try all possible join orders.

Why joins are expensive?

Joins are a costly database operation because they require creation of a cartesian product in memory. This means that a virtual table is created in memory that has a number of rows that is a multiplication of the number of rows from all the tables that you are joining.

Why RDBMS is not scalable?

RDBMS systems guarantee consistency. Sharding makes the system tolerant to partitioning. From the theorem follows that the system can therefor not guarantee availability. That’s why a standard RDBMS cannot scale very well: it won’t be able to guarantee availability.

Is join faster than two queries?

Generally, joins will be faster but with many exceptions. Best thing to do is to check out the query plan for each in your situation. @David – Correct answer though! The join does not automatically produce 20 “fields” as long you only select the columns that you want.

Is join inefficient?

No. Despite the protests of NoSQL proponents, joins are not inherently slow in Relational database systems. Joining two or more tables will certainly take more resources and runtime than just querying one of the involved tables, after all there will be more data to plod through.