RYAN MATSUMOTO: Cloud Bigtable is Google Cloud's NoSQL
database designed to handle large analytical and
operational workloads.
It's used by many companies across a diverse array
of industries, including fintech, adtech, gaming, IoT,
and more.
So how do you know if Cloud Bigtable is right for you?
Today, we're highlighting three industries
that rely on Bigtable to solve challenges, reduce
costs, and accelerate innovation to deliver a great experience
for customers.
Stay tuned.
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In our last episode, we covered why Bigtable is a great option
to hit the optimal balance between speed, scalability,
and reliability for your database.
In this episode, we're going to connect the dots
to show you how Bigtable can be used to solve problems
in areas like retail, transportation, and fraud
detection.
First up, retail.
Say you're a major retailer that manages hundreds of stores
and millions of products.
Bigtable's scalability can help you
handle the massive amount of data that needs to be stored.
You can store data in Bigtable's NoSQL key-value format.
Each row might represent an individual item
at a specific store, with the key being
a combination of the item ID and location,
and columns being the price and the ID
of the person who updated it.
It's also important to be able to support
a large number of reads per second,
since you'll likely have many concurrent requests
from tens of thousands of registers,
as well as from the online store.
Bigtable has you covered with the ability
to support millions of requests per second.
And finally, low latency is a must-have.
You wouldn't want customers to have
to wait a while for employees to retrieve prices during a sale.
This isn't a problem with Bigtable,
though, since it has latency on the order
of single-digit milliseconds.
Next, we have transportation.
Imagine you're a public-sector employee working on a dashboard
to display real-time information about a city bus system.
This use case requires you to have a database like Bigtable
that can handle a massive amount of throughput,
since you'll want to store and retrieve data for thousands
of buses minute by minute.
Bigtable's low latency is also important,
since riders need to get accurate bus information
as quickly as possible.
Bigtable's data model also makes it easy
for you to store time series data about bus locations.
Your data set might include a row for each bus,
with trip ID as the row key, and columns
for origin ID, destination ID, latitude, and longitude.
At the intersection of each row and column combination,
you can have multiple cells, with each cell representing
a different version of the data at a given timestamp.
In this example, you can easily store timestamp values
for latitude and longitude at different times of the day.
Another use case for Bigtable is fraud detection.
Fraud detection companies need to be
able to quickly and reliably tell clients whether or not
they should charge a credit card.
When a transaction comes in, you can quickly
pull the customer profile from Bigtable with low latency
and make that decision.
Scale is another important consideration.
Maybe you have a major client with thousands of stores,
billions of dollars of revenue per year,
and millions of transactions per day.
Thanks to Bigtable's scalability,
you can store up to petabytes of data in the cloud
and keep up with all the requests that
now come in from this client.
And since Bigtable is a fully managed service,
you can seamlessly scale up and down with zero downtime.
And finally, machine learning can help improve the fraud
detection process.
Data can be inputted into an ML model to get a prediction,
but can also be used to further train the ML
model for future predictions.
For this ML pipeline to work, data
needs to be read and written to the database
continuously for millions of requests per day,
making Bigtable a great option because of its high throughput.
So there you have it, a dip into the benefits of Bigtable's
speed, scalability, and reliability
in retail, transportation, and fraud detection.
Bigtable's speed means that it can support millions of reads
and writes per second at low latency.
Scalability means that you can quickly scale up your database
by adding Bigtable nodes that add 10,000 additional requests
per second at no downtime.
And reliability means that Bigtable adds up to 99.999%
availability SLA.
This video is just a sampling of the many industries and use
cases where Bigtable helps companies solve problems
and grow their businesses.
So if you're curious to learn more,
follow the links below for more information.
Thanks for joining us today, and stay
tuned for more episodes about Bigtable.