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Asymptotic notation is the standard way of measuring the time and space that an algorithm will consume as the input grows. In one of my last guides, I covered "Big-O notation" and a lot of you asked for a similar one for Asymptotic notation. You can find the [previous guide here](/guides/big-o-notation). |
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![](/guides/asymptotic-notation.png) |
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[![](/guides/asymptotic-notation.png)](/guides/asymptotic-notation.png) |
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Here is the [original tweet](https://twitter.com/kamranahmedse/status/1243861514907418624) where this image was posted. |
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Big-O notation is the mathematical notation that helps analyse the algorithms to get an idea about how they might perform as the input grows. The image below explains Big-O in a simple way without using any fancy terminology. |
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![](/guides/big-o-notation.png) |
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[![](/guides/big-o-notation.png)](/guides/big-o-notation.png) |
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Here is the [original tweet](https://twitter.com/kamranahmedse/status/1235708842610212864) where this image was posted. |
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Random numbers are everywhere from computer games to lottery systems, graphics software, statistical sampling, computer simulation and cryptography. Graphic below is a quick explanation to how the random numbers are generated and why they may not be truly random. |
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![](/guides/random-numbers.png) |
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[![](/guides/random-numbers.png)](/guides/random-numbers.png) |
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Here is the [original tweet](https://twitter.com/kamranahmedse/status/1237851549302312962) where this image was posted. |
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The chart below aims to give you a really basic understanding of how the capability of a DBMS is increased to handle a growing amount of load. |
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![](/guides/scaling-databases.svg) |
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[![](/guides/scaling-databases.svg)](/guides/scaling-databases.svg) |
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Here is the [original tweet](https://twitter.com/kamranahmedse/status/1234209674003611650) where this image was posted. |
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[![](/guides/ssl-tls-https-ssh.png)](/guides/ssl-tls-https-ssh.png) |
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Here is the [original tweet](https://twitter.com/kamranahmedse/status/1252717722724642822) where this image was posted. |
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