At Precognitive, we were able to start with a blank technology slate to support our fraud detection software products. When we started building the initial version of our platform in 2017, we had some decisions to make: What coding language to use? What cloud infrastructure provider to choose? What database to use? The majority of the decisions were straightforward, but we struggled to decide upon a database. We had plenty of collective experience with relational databases, but not with a wide-column database like Cloud Bigtable—which we knew we’d need to scale our behavior and device workloads. At launch, our products were supported by a self-managed database, but we quickly migrated to Cloud Bigtable, and we love it.  

To efficiently support our bursty, real-time fraud detection workloads, we needed a cloud database that could satisfy the following key requirements:

• Stability to keep up with increased adoption of our products
• Intelligent scaling that avoids bottlenecks
• Native integrations with BigQuery and Cloud Dataproc
• Managed services that free up our engineers’ time to work on our products

Adding Cloud Bigtable as our performance database

As we scaled our services and added customers, our data collection services for our Device Intelligence and Behavioral Analytics products were seeing thousands of events per second. Cloud Bigtable provided a stable managed database that could handle the volume we were receiving during peak hours. We weren’t always able to handle this scale, as an early version of our product utilized a self-managed database.

Every month, two or three engineers spent hours managing the database instances. Whenever the instances crashed, it would cost at least one engineer a day or two of productivity attempting to restore the instances and recovering any data from our backup database. Managing this database internally was taking precious time away from product development.

We circled back to Cloud Bigtable. After two weeks of R&D, we decided to switch the Device Intelligence and Behavioral Analytics services to Cloud Bigtable.

Cloud Bigtable solved our scaling issues. Cloud Bigtable had been attractive to us from the start because it was fully managed, and offered regional replication and other features we were lacking in our own managed instances. Cloud Bigtable provides horizontal scaling and automatically rebalances row keys (equivalent to a shard key) over time to prevent “hot” nodes. In addition, Cloud Bigtable provides a connector to BigQuery and Cloud Dataproc that allows us to analyze the terabytes of data we are processing and use that data for unsupervised machine learning.

The perks of using Cloud Bigtable

After the migration to Cloud Bigtable, we noticed a number of additional benefits: improved I/O performance, a significant cost reduction, and a sizable decrease in hours spent on database maintenance.

We measured some of our typical metrics before and after implementing Cloud Bigtable. Our request latency dropped by about 30 ms on average (to sub-10 ms) for API requests. Prior to the change, we were seeing latencies of 40+ ms on average. This latency drop on our Behavioral Analytics and Device Intelligence products allowed us to trim about an additional 10 to 15 ms off our average response time across all dependent services.

Before we moved to Cloud Bigtable, we had to scale our database instances every time a new customer was onboarded. We were over-scaling in an attempt to avoid constantly resizing our database servers. By sunsetting our self-managed database and switching to Cloud Bigtable, we cut database infrastructure costs by approximately 35% and can now scale as needed, with a couple of clicks, during onboarding.

We have spent zero hours managing a Cloud Bigtable database since launch, and we put the time we are saving every month toward product development.

Moving forward with Cloud Bigtable

As an engineering team, we love working with Cloud Bigtable. We are not only seeing improved developer experience and reduced latency, which keeps the engineers happy, but also reduced costs, which keeps the business happy. We’re able to build more product, too, with the time we’ve saved by switching to Cloud Bigtable. Stay tuned to our engineering blog for more on the lessons we’ve learned and our contributions to the wider Cloud Bigtable community.

Small and medium-sized businesses and enterprises are the backbone of the US economy generating more than 44% of GDP¹. Yet these organizations are still underserved when it comes to online financial tools—and dealing with payments is no exception. Complaints include hidden fees, limited capabilities, long-term lease agreements, and poor customer service.

These are the issues that we wanted to solve when we launched Helcim in 2020 in Calgary (Alberta, Canada). We provide a payment service that offers low rates through our interchange plus pricing model, no monthly fee for the core payments offering, and numerous payment options, as well as simple, affordable hardware such as card readers. 

Our digital-first approach makes it easy for owners of small and medium-sized businesses to get started. Online sign-up means no paperwork and near instant access to Helcim’s software and all-in-one platform experience. Merchants can choose from a range of payment solutions from the Helcim app including in-person payments, SMS payment requests, online invoices with pay now buttons, and more. 

To achieve our goals, we built most of the business systems and processes in-house including our technology stack, financial partnerships, marketing, and everything in between. This is something that few startups would dare to do, but it enabled us to build a payments platform offering the rich capabilities and performance SMBs really need.

Taking control with the cloud

Before migrating our infrastructure to Google Cloud, it was hosted at two colocation data centers in Calgary. This model served us well, but as we grew, most of our hardware needed to be replaced to maintain service security and performance.

A successful round of Series A funding also impacted our trajectory. Giving us the fuel we needed to scale and innovate faster. When we considered the choice between making a large capital investment in our existing environment, or to transition to the cloud, the decision was clear: The cloud was the way to go.

We looked at other big names in cloud hosting and tested another platform. But Google Cloud is by far the best environment for us. It’s much easier for a lean technology team to manage, as we embark on our first cloud strategy. It also offers all the tools and advanced machine learning capabilities we need.

Google Cloud also comes with the backing of Alphabet, a business that in the past five years has spent more on research and development than any other organization in the S&P 500². The ability to engage the Google Workspace account team for guidance to improve our everyday processes was another bonus. 

A variety of investment and training programs from Google Cloud also influenced our decision. We participated in Google for Startups Accelerator Canada which gave us access to Google Cloud experts across all our technology domains. This helped accelerate our infrastructure migration while ensuring we optimized every service from day one. We were also eligible for $100,000 USD of Google Cloud credits, covering our Google Cloud costs which helped us get everything up and running cost-effectively. The partnership with the wider Google team has been extremely impactful as we stand everything up for our business.

But ultimately, it’s the sheer depth and breadth of the Google Cloud environment that makes the difference. Here are the Google Cloud tools we currently have at Helcim.

BigQuery

We chose BigQuery because it is easy to aggregate new data and apply the right access controls. It also delivers outstanding performance running our analytics workloads.

Vertex AI

Vertex AI makes the deployment of new models exponentially faster, and with Google Cloud, we can do most of the work through containers instead of proprietary tooling.

GKE

GKE has enabled us to migrate to a fully managed cloud service and avoid a lift-and-shift exercise that would have prevented us from getting the full benefits of a containerized infrastructure. Running a new GKE environment also enabled us to significantly reduce platform latency by 20%-50%. We can now deploy projects in hours instead of days. 

Cloud Storage

We updated our centralized file system to use Cloud Storage, which is faster and more scalable.

Cloud SQL

All of our software today is built on top of MySQL, so CloudSQL was the natural choice for cloud database management.

Cloud Run

Cloud Run is more flexible than other serverless tools and was an easy way to reduce the burden of managing some of our services.

Boosting performance across the business

By migrating to Google Cloud, we transformed our application performance. We were able to decouple the infrastructure between systems and use modern server hardware for our compute and database instances. With very little change to our code, we saw a 50%+ increase in the speed of our entire platform.

Giving developers more control of the technology running their systems via containers means that they can enhance systems through more frequent language updates and by deploying new technologies to optimize workloads.

We can more closely monitor our systems to diagnose issues and fix their root cause faster. Being able to quickly add resources gives us further options if we experience platform latency or increased traffic.

Maintaining momentum with machine learning

Leveraging Vertex AI has significantly reduced the time it takes the team to build and deploy new machine learning models. Greater agility in our data stack has also freed up time for exploratory work in the data team. For instance, by creating low fidelity proxy data for human behavior in the application process, we created a new model that will reduce the number of manually reviewed batches by more than 10%.

We’ve also been able to improve our deployment process and the time to rollback. As a result, breaking changes in production have been reduced from more than five minutes to less than 30 seconds.

Thanks to BigQuery, we can make better use of data to support key business decisions. Previously it was hard to aggregate data from different sources and while maintaining our strict requirements for customer data confidentiality. We also needed specialist SQL knowledge to consume it. By investing in a more modern data stack, the availability of trusted data across the organization has increased exponentially. 

We’ve also overcome the constraints imposed by static hardware environments especially when maintaining a high-availability configuration between two locations. With Google Cloud, we’re no longer constrained by such a rigid arrangement and the deployment velocity of new infrastructure tooling has been reduced from months to days.

Security is another area where Google Cloud excels. From hackers and fraudsters to bots and web attacks, it protects our users, applications, and data, while facilitating compliance with local and regional authorities. We can also integrate more easily with our security partners ensuring that we can empower our team to stay ahead of cyber criminals and other external threats.

Building the payments platform for the future, today

When we look to the future, Google Cloud opens the door to dozens of opportunities to widen our appeal to SMBs while remaining competitive. Its advanced infrastructure for cloud computing, data analytics and ML supports our roadmap to profitability and will help us attract future rounds of funding.

Above all it provides a foundation for growth. We grew 400% in 2021 and raised more capital in the spring of 2022 to grow even faster. In 2022 we were also listed as one of the top payments processors by industry publications such as Nerdwallet and Merchant Maverick. With Google Cloud, we can build on this success, continue to innovate, and help our SMB customers take their payments and e-commerce strategies to the next level. 

If you want to learn more about how Google Cloud can help your startup, visit our page here to get more information about our program, and sign up for our communications to get a look at our community activities, digital events, special offers, and more. 

To learn more about Google for Startups Accelerators and to apply to a program in your region, visit the website here. 

^{1. Small Businesses Generate 44 Percent Of U.S. Economic Activity
2. Alphabet: Big Value In Big Tech}

Cloud migration is top of mind for most companies with SAP applications. While the advantages of the cloud for SAP customers is generally understood, the move itself can be complicated and disruptive. So what actually are the business benefits and cost savings? How long will it take to recoup such an investment? Two recently published reports from Forrester and IDC can help to quantify the benefits and ROI. 

Getting answers to the million-dollar questions
Forrester and IDC bring different methodologies to the table; they asked somewhat different questions and used different models to calculate their financial KPIs. This allows you to get two different points of view on the same basic questions about value, risk, and ROI.

As it turns out, both reports found that customers who migrate their SAP environments to Google Cloud see an impressive return on their investments. From uptime and infrastructure to efficiency and productivity—both Forrester and IDC identified major benefits to companies that have made the move to Google Cloud.

Let’s walk through some of the highlights from both reports.

Forrester’s TEI model spotlights the power of uptime improvements
Based on in-depth conversations and quantitative research with six companies, here are the key findings from the Forrester Total Economic Impact (TEI) study for companies running SAP systems on Google Cloud: 

• Direct cost savings. When they compare cloud subscription and related costs to what they spent on legacy systems and infrastructure, most IT leaders expect a cloud migration to deliver up-front savings. But according to Forrester, the companies interviewed reported average savings of more than $3 million a year, including eliminated hardware purchases, right-sized software licensing, staffing efficiencies, and other operational cost savings.

• Dramatically improved uptime. Customers told Forrester that migrating SAP to Google Cloud pretty much eliminates downtime—planned or unplanned—as a significant IT concern. According to Forrester, companies realized an average of $1.5 million in savings per year by avoiding the revenue and user productivity losses that had once been a fact of life for their IT teams.
• Significant efficiency gains. Because Google Cloud works to mitigate performance bottlenecks, infrastructure mishaps, network delays and more, the companies Forrester interviewed reported a yearly average of $500,000 in productivity gains for SAP business users and frontline workers.

Companies also reported an annual average of $500,000 in additional IT efficiency gains after migrating SAP to Google Cloud. This quantifies what happens when IT practitioners no longer have to deal with the bottlenecks that come with legacy systems, and are able to spend their time on tasks that actually build value and help the business. Based on the Forrester analysis, the companies interviewed could expect average three-year net benefits of about $15.4 million.

“We benefit from any technical innovation in the infrastructure area because Google Cloud is doing that for us,” one customer told Forrester. “So, whenever there’s new hardware available or new processes or whatever, I don’t have to run the specific project to migrate from A to B.” 

IDC finds that good things happen when SAP downtime is reduced 
The IDC report highlights four areas where Google Cloud generates the most value for customers:

1. Cutting infrastructure costs. According to IDC, customers running SAP on Google Cloud spent 31% less on infrastructure each year, or an average of $233,000 less per company. The ability to scale SAP environments dynamically and to keep them right-sized was a major factor; so were the advantages of automated infrastructure monitoring and savings on software licenses once these companies could stop overprovisioning.

2. Giving a team better things to do. IDC found that the infrastructure, database, and security teams of the companies they interviewed reduced the time they need to maintain and manage SAP environments by an average of 66% per year, for a savings of $443,000, per company. As a result, these companies got the equivalent of a major staff expansion from their SAP migrations—giving them both the staff time and the expertise to focus on far more valuable activities.

3. Limiting unplanned downtime. These companies reported to IDC an average 98% reduction in unplanned downtime. Migrating SAP to Google Cloud significantly reduces the threat of downtime and saves the business an average of nearly $770,000 per year in lost revenue and user productivity. For some firms, the downtime savings topped $1 million per year.

4. Making users more productive. The companies interviewed told IDC that by avoiding downtime and disruptions associated with upgrade and maintenance tasks for their legacy SAP systems, they saved an average of $363,000 annually in user productivity. But there’s an even more interesting under-the-hood stat contributing to these gains: These companies reduced the time required to deploy new SAP compute and storage resources from an average of 8.8 days to 1 hour.

When IDC added up these and other savings associated with running SAP on Google Cloud, it found an average three-year savings of more than $3.5 million and a five-month payback period. 

“We acquired another company, so basically overnight we needed to be able to deal with that increase,” said one customer IDC spoke with. “We doubled our footprint overnight, and we had to take on hundreds of additional employees. We needed a platform that we could easily scale up if we required, and that’s the benefit of running SAP on Google Cloud for us.” 

Explore the reports
There is a lot to think about when considering a move of SAP systems to the cloud. The cloud has many advantages, but migration can seem complicated and tricky; we appreciate that you are looking to understand the full picture. These papers are a great place to start. 

Download the reports—Forrester’s “Total Economic Impact of SAP on Google Cloud” and IDC’s “Business Value of SAP for Google Cloud Environments.” Then, get in touch.