Big data was a reference to thinking about the problem in terms of the speed of the hardware. If it's 1000x slower than what the hardware can do, that's a sign you're using the wrong tool for the job.
Getting within 10x is reasonable, but not 100x or 1000x, which is VERY COMMON in my experience. These two situations are very common:
1) SQL queries that are orders of magnitude slower than a simple offline computation in Python or R (let alone C++). The underlying cause is usually due to bad query planning of joins / lack of indices.
You might not have the ability to add indices easily, and even if you did, that has its drawbacks for one-off queries.
2) You need to do some computation that's awkward inside SQL. Statistics beyond basic aggregations, iterative computations (loops), and tree structures are common problems.