Size of database and choice of databse

Hi all, currently working at startup and we have started to face scaling issues. Example Database tables have started increasing rows. So how do you handle this kind of data? How to think in the direction of improving and writing queries on billions of records to perform optimal? Can people with experience help me with any resources or personal experience they have gone through when going from 1 to 100? Minor of the minor suggestions would help. Grateful and thanks to all in advance.🙌

Going through the job posting I've seen this sentence pop up in the requirements multiple times: "Have delivered, extended, and maintained large scale distributed systems." I'm having a hard time understanding what this means in a job context. Can anybody explain with like a simple example of delivering a distributed system that would make them eligible for this requirement? If I'm working on a webapp that uses tech like kaftka and zookeeper, can I consider myself as meeting this requirement?

Hi all , Has anyone worked on large scale es indices greater than 500 gb of data. need to ask few questions Thanks

I work for a growing startup in Bangalore. The data team size is very small with no data lead. Not a single query we hit the DB gives any result. Owing to cost cutting my firm has cut down the instance size and they're planning to downgrade the DB too. We data analysts are relying on the data engineering team to fetch us results for our queries which takes a long time to get a single table. This is highly inefficient. The data size is growing at a massive scale however the analytics efforts are trickling down due to poor infrastructure. Is this happening in your data team too? How can I solve this problem given there are no experienced data leaders in our firm to voice out.

Actual job: export these 1894 user emails into an excel sheet for marketing by EoD please

We have our database and data in MySQL local machine. Monthly data storage and fetch is <1M rows. would like to migrate this to AWS. how do we do this? Would like to explore free credits service provider until we exhaust and explore. Intent to maintain a centralised database and running queries.

Before you go about how "stack isn't important, skill is", the purpose of this post to understand what the current market trend is for backend. A bit about me, I'm a backend dev with experience in Node.js, MySQL and MongoDB. Around 4 YoE. My goal is to work in a company that serves customers at scale, and to learn how to engineer at scale. If you work in such a company / know someone who does, what stacks are you/they using and how are they using it? I'm seeking answers in terms of language, DB, cloud providers, etc.