I used load data command in my sql to load the data to mysql table. ... Can MySQL can handle 1 Tb of data were Queries per sec will be around 1500 with huge writes . However, occasionally I want to add a few hundred records at a time. Load-wise, there will be nothing for hours then maybe a few thousand queries all at once. If it could, it wouldn't be that hard to find a solution. When I have encountered a similar situation before, I ended up creating a copy/temp version of the table and then droped the original and renamed the new copy. I gave up on the idea of having mysql handle 750 million records because it obviously can't be done. The SELECT's will be done much more frequently than the INSERT. Yes, PostgreSQL incremented number of clients by 10, because my partners did not use PgBouncer. This Chapter is focused on efficient scanning a large table using pagination with offset on the primary key. The file is in csv format. it has always performed better/faster for me when dealing with large volumnes of data (like you, 100+ million rows). Rather than relying on the MySQL query processor for joining and constraining the data, they retrieve the records in bulk and then do the filtering/processing themselves in Java or Python programs. If you’re not willing to dive into the subtle details of MySQL query processing, that is an alternative too. You can handle millions of requests if you have server with proper configuration. eRadical. It is skipping the records after 9868890. Thanks towerbase for the time you put in to testing this. And with the Tesora Database Virtualization Engine, I have dozens of MySQL servers working together to handle tables that the application consideres to have many billion rows. This is also known as keyset pagination. For MySQL incrementing number of clients by 10 does not make sense, because it can handle 1024 connections out of the box. InnoDB buffer pool size is 15 GB and Innodb DB + indexes are around 10 GB. IF YOU WANT TO SEE HOW MYSQL CAN HANDLE 39 MILLION ROWS OF KEY DATA Create a table, call it userlocation (or whatever you want) Then add a column "email" and "id", make the email 100 Varchar, and id 15 Varchar. On a regular basis, I run MySQL servers with hundreds of millions of rows in tables. Remember, this is all you need, you don't want extra stuff in this table, it will cause a lot of slow-down. Server has 32GB RAM and is running Cent OS 7 x64. I modified the process of data collection as towerbase had suggested but I was trying to avoid that because it it ugly. I have one big table which contains around 10 millions + records. either way this would produce a few read queries on the vouchers table(s) in order to produce listings and id-based updates/inserts/deletes. I have .csv file of size 15 GB. The solutions are tested using a table with more than 100 million records. 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