Video 4AVQchL9tTo

[00:00] This is not yet another cloud comparison video. I'm not just going to be giving you a basic overview of each provider. Instead, we are going to be comparing Amazon with services, AWS, Microsoft Azure, Google Cloud Platform, GCC,

[00:15] on a number of key factors and really diving into the details. So, grab your coffee or your favorite beverage, sit back, and let's get started. My name is Elias, I'm a Senior Solutions Architect. Now let's do this.

[00:30] First up on the list we have Amazon Web Services, also known as AWS. This is the oldest and the most established cloud provider having been launched back in 2006.

[00:43] AWS offers a wide range of services including compute and storage databases, as well as machine learning and Internet of Things capabilities. It's also the most popular cloud provider today with the largest market share.

[00:57] Next, we have Microsoft Azure. Azure was launched in 2010 and offers similar services to AWS, including compute and storage and databases. It also has a strong focus on hybrid cloud capabilities, allowing customers to easily

[01:13] connect on-premise infrastructure with Azure services. Azure also has a strong integration with other Microsoft products such as Office 365 and Dynamics 365. Lastly, we have Google Cloud Platform or TCP.

[01:28] Now, GCP was launched in 2011, just one year after Azure, and offers similar services to AWS and Azure including, again, compute, storage, and databases. And GCP has a strong focus on big data and machine learning, with services like BigQuery

[01:43] and SyscalFlow. It also offers a strong integration with other Google products, such as Google Analytics and Google Maps, for example. So let's start our comparison with pricing. AWS is known for having a vast array of products and services to choose from,

[01:59] but their pricing structure can be a little complex and difficult to navigate. Azure, on the other hand, has a more straightforward pricing model and often offers discounts for long-term commitments,

[02:12] which can make it a good choice for businesses with predictable workloads. And GPP has a reputation for being the most cost-effective of these three, especially for those who are willing to do some optimization to get the best prices.

[02:27] Next, let's take a look at the range of services offered. AWS has the most comprehensive offering of the three, with a huge number of products and services that can be tailored to fit almost any need.

[02:40] Azure comes in second in this regard, with a solid selection of services that are particularly well suited for enterprise customers. And GCP is a bit more focused with a smaller range of services that are geared more towards developers and startups.

[02:56] Keep that in mind, we'll get back to it later in the video. Now I have heard folks complain about how the AWS web console is overwhelming. So that got me thinking about comparing the web consoles next.

[03:08] And it seems all three major cloud providers offer user interfaces and comprehensive documentation to help users get started However in terms of web console ergonomics there are some differences between the three providers First AWS offers a comprehensive web console with a wide range of

[03:29] services, but I agree, it can be overwhelming for beginners. The console is highly customizable and allows users to create custom dashboards, but it can also take some time to navigate and find

[03:42] the specific services you need. On the other hand, Azure Web Console is considered to be more intuitive and easy to use compared to AWS with a more streamlined interface and clear navigation. The console also offers a wide range of services but it's more focused

[03:59] on Microsoft-specific products and services. Now, GPC's Web Console is considered to be the most user-friendly of the three with a clean, simple interface that makes it easy

[04:11] beginners to find and use the services they need. The console offers also a wide range of services but it's more focused on big data and machine learning. So it seems that overall all three

[04:23] cloud providers offer user-friendly with consoles but Azure and GCT are considered to be more integrated and more beginner-friendly or user-friendly than AWS. Let's talk about

[04:36] Internet of Things next. As a subject I'm very interested in personally as a thinker. So I went on the hunt trying to find which out of the major three cloud providers is well positioned in the IoT domain.

[04:50] And we'll start with AWS. Well, it offers a comprehensive set of IoT services including AWS IoT Core, Greengrass, IoT Analytics. These services provide a wide range of capabilities for IoT deployment, such as device management,

[05:05] data collection and processing, machine learning. However, the complexity of these services can be overwhelming for beginners. Azure IoT, on the other hand, is considered to be just more beginner-friendly compared

[05:19] to AWS, with a more streamlined interface and a focus on ease of use. Azure IoT Central is a fully managed SaaS solution that allows users to connect, to monitor, and to manage IoT devices without requiring any cloud expertise.

[05:36] GCT also offers a wide range of IoT services, including IoT Core, Cloud IoT Edge, and Cloud IoT Devices UK. But it seems GCT's IoT services are focused on data analytics, on machine learning, and on edge computing.

[05:51] Google's IoT services is considered to be easy to use and beginner friendly, but not as comprehensive, not as complete as AWS or Azure. But wait, did you start to hold this pattern here? It seems that no matter what fields we look at, Azure is considered to be most beginner friendly,

[06:10] AWS the most comprehensive set of services, while GTP is considered to be easy to use, but with a focus on data analytics and machine learning. But I was not convinced, not yet. So I set out to research yet another aspect, their SDKs, the software development case, and how easy it is for their customers to build and integrate applications with their respective cloud services.

[06:34] But that was almost a waste of time because they pretty much turned out to score the same All the three provide SDKs that support various programming languages such as Java Python Node Go Ruby and many many more

[06:51] All the three provide a convenient way to interact with their services and all the three provide a CLI, a command line interface that allows developers to access their respective services

[07:03] using the command line command. So I quickly moved on to the next item on my list which is databases. I wanted to learn which one was offering the best database services allowing the customers to store, to manage, access their data in

[07:18] the cloud. So here we go. AWS seems to have thought about every single data storage use case you can think of and created a managed service for it. This is

[07:31] very obvious when you look at their purpose-built database webpage. Whether it's relational, key value, in-memory database, white column, graph, time series, or even ledger, you can always find a

[07:43] fully managed database service at AWS. And Azure was actually not very far behind offering similar services at AWS such as Azure SQL Database, a fully managed relational database service,

[07:59] Azure Cosmos DB, a fully managed NoSQL database service, and Data Lake Storage, a fully managed data-like service, obviously. Now, Azure also offers Azure database for MySQL, Azure database for Postgres, which are

[08:15] fully managed relational database services. As for GCP, well, it follows in the steps of the aforementioned providers by offering services like Cloud SQL, a fully managed relational database service that supports popular database

[08:29] engine such as MySQL. By the way, I think it's pronounced MeSQL. I read somewhere that the creator of the database has two girls. One is me and the other one is Mariah. So I think it's actually MeSQL,

[08:46] not MySQL. Anyway, it supports MySQL, PhotographSQL, and SQL Server. There's also Cloud Spanner, a globally distributed relational database service, there's Cloud Bigtable, a fully managed

[09:00] NoSQL database service, and there's Cloud Datastore, a fully managed document database service. GCT also offers Cloud Firestore, a fully managed cloud native NoSQL document database service.

[09:14] That was a mouthful. And for the last item on my comparison list, I wanted to explore a domain I'm not very familiar with the no-code slash low-code area that's taken the world by a storm recently

[09:28] since the public release of chat gpt and all the ai tools around it so when it comes to creating and deploying applications without writing code slash writing the least amount of code possible aws offers

[09:42] a wide range of such services including aws uprunner which allows customers to build test and deploy containerized applications quickly and easily. Get AWS CokeStar which allows customers to quickly develop build and deploy applications on AWS And AWS Honeycode which is built to simplify manual tasks No programming required As for handling data with no code AWS offers AWS Blue ETL service

[10:09] which enables customers to extract, transform, and load data for analytics and data warehousing through a series of pleasant calls. Azure seems to follow suit as well by offering similar no-code services at AWS,

[10:22] Azure Logic Apps, a service that allows customers to create workflows to automate business processes and integrate with other Azure services. And then also Power Automate, which allows customers to automate business processes

[10:36] and integrate with other services. This one actually was suspiciously similar to AWS Honeycode.

[10:48] Azure also offers Azure Databricks, which allows customers to build, train, and deploy machine learning models without writing code. And as for GCPs, I can only find one cloud service.

[11:01] That was the Cloud Dataflow, which allows customers to build, to test, and deploy data processing pipelines without writing code. So maybe someone who is knowledgeable about GCP can chime in in the comments with more GCP no-code services that I'm going to submit.

[11:17] Now at this point, I was exhausted. My goal was to try to find an area where there was a clear winner. But the same patterns keep occurring. Regardless of which domain I looked at, AWS turned out to be more complete, Azure more

[11:31] user-friendly, and GCP more easy to start with. But I had to take some time to think about this. And after a while, I realized how each of these providers has its own unique strengths

[11:44] and weaknesses. AWS is known for its reliability and robustness with a long track record of uptime and a huge network of data sensors around the world. Azure is particularly strong in the areas of artificial intelligence and internet and offers a number of tools and services to support these applications.

[12:03] And GPP is a great choice for those who want a more open and flexible platform with a wide range of open source tools and technologies available. So, which one is the best?

[12:15] Well, it really depends. I know you hate this answer, but it really depends on what you read, honestly. If you're a large enterprise with deep pockets and a need for a wide range of services, AWS

[12:27] might be the way to go. If you're a developer or a startup on a tight budget, JCT could be a great fit. And if you're somewhere in the middle, Azure then might be the perfect compromise. But, you know, don't take my word for it.

[12:41] important to do your own research. It's important to figure out the cloud provider that is the right fit for your specific needs. And that's where we come in. We will be doing a series of videos digging into each of these providers in more depth. So stay tuned. Thank you very much for

[13:07] and don't forget to hit that subscribe button to stay up to date on all things Clouds and Shooting. See you in the next video. Peace out.