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Data Structures Cheat Sheet

In this article, we will provide an introduction to data structures, offering examples of each structure and illustrating how they could be represented in Memgraph. Among these structures, graphs stand out as non-linear data structures composed of a finite set of nodes, connected by relationships. @javascript_resources
They are used to tackle real-world problems in areas such as networks, knowledge graphs or fraud detection cases.

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For all Data Engineers out there, here is The State of Data Engineering 2024

Some of the highlights:

✅ More and more, data observability tools are used not just to monitor data sources, but also the infrastructure, pipelines, and systems after data is collected.

✅ Companies are now seeing data observability as essential for their AI projects. Gartner has called it a must-have for AI-ready data.

✅ Like in 2023, Monte Carlo is leading in this area, with G2 naming them the #1 Data Observability Platform. Big organizations like Cisco, American Airlines, and NASDAQ use Monte Carlo to make their AI systems more reliable.

How Facebook served billions of requests per second Using Memcached

There are two absolute truths about running a social network at the scale of Facebook:

First, it cannot go down.

Second, it cannot run slow.

These two factors determine whether people are going to stay on your social network or not.

Even a few people leaving impacts the entire user base because the users are interconnected. Most people are online because their friends or relatives are online and there’s a domino effect at play. If one user drops off due to issues, there are chances that other users will also leave.

Facebook had to deal with these issues early on because of its popularity. At any point in time, millions of people were accessing Facebook from all over the world.

In terms of software design, this meant a few important requirements:

Facebook had to support real-time communication.

They had to build capabilities for on-the-fly content aggregation.

Scale to handle billions of user requests.

Store trillions of items across multiple geographic locations.

To achieve these goals, Facebook took up the open-source version of Memcached and enhanced it to build a distributed key-value store.

This enhanced version was known as Memcache.

Memcached is an in-memory key-value store that supports a simple set of operations such as set, get, and delete.

The open-source version provided a single-machine in-memory hash table. The engineers at Facebook took up this version as a basic building block to create a distributed key-value store known as Memcache.

In other words, “Memcached” is the source code or the running binary whereas “Memcache” stands for the distributed system behind it.


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