Podcast: Learn More About the TigerGraph Cloud July 2022 Release
This transcript is an abbreviated version of the podcast featuring Kiran Kamreddy talking about the July 2022 release of TigerGraph Cloud published on Wednesday, July 27, 2022.
Today we’re going to be speaking to Kiran Kamreddy, Director of Product Management at TigerGraph, we’re gonna be talking a little bit about the recent launch of TigerGraph cloud. So Kiran, can you do me a favor and tell us a little bit about yourself and what you do at TigerGraph?
Thanks for inviting me to the podcast. I’m responsible for building up our cloud portfolio here at the company. I’ve been here at the company for about a year now. And with the help of the great team that I have all around we’ve introduced some groundbreaking capabilities into our products.
The launch of TigerGraph Cloud was such a big one and so well received by customers and internally in the company. So why is it important for companies thinking about graph to think about the cloud in today’s environment?
I did similar jobs at two companies previously, building up the cloud product offerings based on their on-prem software. I think cloud, the term cloud, is a manifestation of different trends that are happening across core technology. And also, more importantly, in the business aspect as well. From a technology standpoint, there are three broad trends. Number one, there is lots and lots of data that is being generated today than ever before, I think pretty much everybody agrees to it. And there is different types of data than we have seen before. And number two, because of the hardware economics that we have today, meaning the storage is much cheaper, the memory is much cheaper, they are able to store a lot of the data and arguably able to process some of the data and able to like get value out of the data. And the third one, which is a big one, is that things are moving more real-time, like there is this phenomenon of wanting it now, wanting it today, versus doing batch kind of processing. This real-time phenomenon, you can see in both operational systems and also in back office systems in terms of being able to detect if something goes wrong, versus detecting something going wrong after the fact that has happened a few days ago. So those are the technology things that I see. And from a business standpoint, I think there is continuous pressure.
And now, because of the times that we are in, there is increased pressure on IT budgets to deliver value or value from the kinds of investments that are going on. And businesses are increasingly looking to become data-driven in terms of how did they build products, how do they serve their customers, and how do they run their internal operations overall. And if you track these two trends across technology and business, it is clear that to be able to take advantage of all this data, the big volumes of data, the big data in general, and to get meaningful value out of it while keeping the budgets under control. We need something that can scale with us. Something that can be consumed only when it is needed and be shut off when it is not needed. And also deliver on its economies of scale and lowest costs overall, that something is cloud. Cloud is the technology that delivers on today’s trends that are happening across tech and business. And I think that’s the reason why you see cloud is undoubtedly an essential element in an IT strategy, is that at most companies today,
Something that you said there piqued my interest. We hear this term, real-time, and we’ve been hearing it for so many years, in relation to business intelligence, in terms of fraud detection, cybersecurity, all those things. But the technology always never seemed like it was able to catch up with real-time; it was always near real-time or as fast as you can get it, but never real-time. Is the maturation of cloud technology finally the thing that’s going to get us over the top to actual real-time analytics and data processing?
I wouldn’t say cloud is the only thing that is needed. But it is a necessary condition. So cloud delivers the value from being able to process the data that is being generated at a very high speed, high velocity, being able to capture the data, and give it to the system that is supposed to do the processing, and also supply the underlying processing capacity that was maybe limited in the days of no cloud, because you can have only so much of a capacity in the data center. But the cloud, the capacity is virtually unlimited. And the capacity grows as the demand on the system grows. So in some ways, for example, if a bunch of people are going and hitting the amazon.com website, during your Thanksgiving shopping time, you need to be able to cater to the demand and then deliver the value and deliver the website in real-time fashion, right. So to do that, a data center kind of limits you in a number of ways. And cloud, because of its inherent ability to scale, to be used only on demand … from an infrastructure standpoint, there’s still got to be the business logic that needs to be in place, the logic to process the things. So cloud solves a lot of the infrastructural problems, but you still need to have the software capable of handling the processing areas and so on.
Focusing back on our release, how is TigerGraph helping these companies thinking about the cloud or transferring some of their operations over to the cloud?
So, as know, TigerGraph is a graph database, a natively built graph database, and it is massively scalable in the sense that like, “Hey, you want a 20 node or 30 node TigerGraph cluster.” TigerGraph is able to like function in that manner, in terms of being able give you that capacity. And then graph database in itself is something that represents the data in its most natural way, something that is not possible in the traditional relational databases. So that is why it has always been a powerful thing. We’ve always had relational databases and other kinds of databases, but graph is very intuitive when it comes to working with data. For example, if you want to know how people are connected to each other, trying to know who is that influential person in the network that can influence the other people involved in the network, given a bunch of people, what are the communities among those people? Trying to see how the manufacturing part is flowing through a supply chain, understanding the routing network to find the optimal transit path for a package. So these are all real-world problems. Data-related problems that have a lot of value to solve for, and graph gives us those intuitive tools to help answer these questions.
So while a graph database solves some really difficult data problems, the cloud makes that solving easier. You obviously need to run the graph software across big amounts of data, which you already may have in the cloud in the form of object stores like S3, Azure, or GCP. And you have to scale your software to be able to work with this data that is already in the cloud. So that is where TigerGraph Cloud is coming into the picture. Meaning, hey, you already have this great software called graph database, which lets you work through the data problems in a very intuitive way. And cloud, the cloud offering of that graph database, makes that solving part even easier, meaning you don’t need specialized knowledge on how to run the software at scale. You don’t need to know the inner workings of the database software to make sure that the software is up and running at all times and deliver the levels of performance that you typically need for your specific workload. All of that is taken care of by the cloud offering so that you, the customer, can focus on running the software and focus on the business problems instead. So we offer a cloud portfolio of offerings. Customers can pick and choose the offering that really solves their own problem.
Can you tell me a little more about the cloud portfolio you just mentioned?
At a high level, there are self managed offerings, and there is a fully managed offering. So let’s talk about the self-managed offering first.
The self-managed offering is where the customer would buy our software from us, and install and run it themselves in their own public accounts with AWS, Azure, or GCP. The word, self-managed, indicates the customer is pretty much responsible for running and operating the software. But the value addition is that we have the inbuilt capabilities in the software that makes it compatible to work on these cloud platforms. There’s also another option in the self-managed space, where customers can just go to the marketplaces, and buy our prebuilt optimized images, which eliminates the step of installation and configuration. But still, the customers have to run and manage this. The installation part, the configuration part, is replaced by a click of a button at the cloud marketplaces.
The second category is our fully managed service, which we call TigerGraph Cloud, which really is a point-and-click environment for our customers, where they don’t really have to worry or care about the infrastructure planning involved. TigerGraph takes care of all the provisioning out of the box. TigerGraph runs the day-to-day operations and makes sure that the software is up to date and running in an optimized fashion to deliver high performance. The customers get a nice and modern user interface to work with.
What is the difference between TigerGraph Cloud and the on-premises version?
There is practically no difference; you get basically the same software capabilities. But there are differences in terms of how you experience and interact with the software. With TigerGraph Cloud, you can get started and be up and running within a few minutes. Go to our website, tgcloud.io, give an email, get yourself an account created!
Would you like to hear more about TigerGraph Cloud? Listen to the podcast for the full conversation, including new features released in the product and the company’s vision for the future of TigerGraph Cloud.