# Where does Julia (ecosystem) provide the greatest speedup, and where does it lag the most behind (compared to e.g. Python)?

**URL:** https://discourse.julialang.org/t/where-does-julia-ecosystem-provide-the-greatest-speedup-and-where-does-it-lag-the-most-behind-compared-to-e-g-python/56565
**Category:** Community
**Created:** [March 5, 2021, 3:22pm UTC](https://discourse.julialang.org/t/where-does-julia-ecosystem-provide-the-greatest-speedup-and-where-does-it-lag-the-most-behind-compared-to-e-g-python/56565 "2021-03-05T15:22:57Z")
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### Author: ![Satvik](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/satvik/32/20486_2.png) [@Satvik](https://discourse.julialang.org/u/Satvik)
#### Post date: [March 6, 2021, 12:00am UTC](https://discourse.julialang.org/t/where-does-julia-ecosystem-provide-the-greatest-speedup-and-where-does-it-lag-the-most-behind-compared-to-e-g-python/56565/7 "2021-03-06T00:00:57Z")

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Here’s my 30x success story: [Julia's applicable context is getting narrower over time? - #5 by Satvik](https://discourse.julialang.org/t/julias-applicable-context-is-getting-narrower-over-time/55042/5) , as someone with years of experience with numpy and ~0 experience with Julia at the time.

Currently I find that Julia really shines anywhere you have a memory bottleneck. It’s also worth noting that profiling is significantly easier in Julia, because it’s “Julia all the way down” – so even in cases where I could achieve the same speedup in Python, it was much easier to find that speedup in Julia.

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