Really, there are three main challenges when we look at scaling relational databases.

实际上，当我们探讨关系的扩展问题时，主要面临三大挑战。

An archetype is more like a relational database.

原更像是关系。

That's why we give people that brick, that's a relational database, and they can build CRM themselves.

这就是为什么我们给人们这块砖，这实际上是一个关系， 他们可以用它自己搭建客户关系管理系統。

And when we talk about horizontal scaling for relational databases, Very often what we're talking about there is sharding.

在讨论关系的水平扩展时，我们通常指的是分片技术。

And additionally, when you're doing that scaling operation, traditionally, relational databases, you're provisioning for peak.

此外，在进行扩展操作时，传统的关系通常是按峰值需求来配置资源的。

The way we set it up makes that possible, because now it's a relational database, so we have development time.

我们设置的方式使之成为可能，因为现在这是一个关系，所以我们有了开发时间。

Relational databases are at the core of many applications and have been for many, many decades.

关系是众多应用序的核心，几十年来一直如此。

However, at some point with a relational database, you tend to bump into scale problems.

然而，在使用关系到一定度时，通常会遇到扩展性问题。

The relational database curriculum, like, I don't know, tens of thousands of people have gone through that and claimed the cert.

关系，我所知， 已有万人完成了学习并获得了认证。

And so it's not like we've forgotten about relational databases.

所以我们并没有忘记关系。

But there are challenges that come with relational databases.

然而，关系也带来了一些挑战。

He architected FreeCodeCamp's entire relational database certification curriculum, which you can run in your browser or right inside of your VS Code editor.

他设计了FreeCodeCamp的整个关系认证，你可以在浏览器中或直接在VS Code编辑器内运行该。

But databases, specifically relational databases, you have to provision for that peak capacity.

但，特别是关系，你必须为峰值容量进行资源配置。

So if you are provisioning a relational database during that time, you're going to have that kind of wasted compute resource.

因此，如果您在那个时间段内配置关系，就会产生那种计算资源的浪费。

And that's great, but for a lot of customers, they want transactional semantics, they want the things you get out of a relational database.

这很好， 但对于许多客户来说，他们需要事务性语义， 需要关系所提供的功能。

These databases, relational database technology, predates cloud compute, where we have these horizontally scaling connection pools that can cause these connection storms very easily and overload the database.

这些关系技术早于云计算时代，在那时我们有这些水平扩展的连接池，它们很容易引发连接风暴并导致过载。

And very often you see the relational database can become the bottleneck and it can become the sticking point as you start to want to scale your application.

通常情况下，随着应用序开始需要扩展，您会发现关系可能成为瓶颈，并成为扩展过中的阻碍点。

So Josh, you've done many, many things in your career, but the thing we're going to focus on today is really about databases and not just any old databases, but relational databases.

那么，乔什，你在职业生涯中涉猎广泛，但今天我们要聚焦的是领域， 而且不仅仅是普通的，而是关系。

Yeah, and this is really the third big challenge that I see with scaling relational databases, is if you've got a good strategy for vertical scaling, you've got a good strategy for horizontal scaling.

是的，这实际上是我认为扩展关系时遇到的第三大挑战：如果你已经制定了良好的垂直扩展策略，并且也具备了有效的水平扩展策略。

The challenge really with auto-scaling your relational database is that If we look at a traditional provisioned database, take for example PostgreSQL, which is one of the most popular relational database engines, open source database engine.

自动扩展关系的真正挑战在于，如果我们看传统的预配置，比如PostgreSQL，这是最受欢迎的开源关系引擎之一。