Cloud Firestore is a NoSQL document database that simplifies storing, syncing, and querying data for your mobile and web apps at global scale.

Cloud Firestore is a fast, fully managed, serverless, cloud-native NoSQL document database that simplifies storing, syncing, and querying data for your mobile, web, and IoT apps at global scale.

Its client libraries provide live synchronization and offline support, while its security features and integrations with Firebase and Google Cloud Platform (GCP) accelerate building truly serverless apps.

Here’s other stuff it’s good at:

Sync data across devices, on or offline

With Cloud Firestore, your applications can be updated in near real time when data on the back end changes. This is not only great for building collaborative multi-user mobile applications, but also means you can keep your data in sync with individual users who might want to use your app from multiple devices.

With Firebase Realtime Database, we felt we had built the best force-plate testing software on the market. Thanks to Cloud Firestore, in only two weeks, we built a system that’s significantly better and includes features we never thought possible to ship on Day 1.

Chris Wales, CTO, Hawkin Dynamics

Cloud Firestore has full offline support, so you can access and make changes to your data, and those changes will be synced to the cloud when the client comes back online. Built-in offline support leverages local cache to serve and store data, so your app remains responsive regardless of network latency or internet connectivity.

Simple and effortless

Cloud Firestore’s robust client libraries make it easy for you to update and receive new data while worrying less about establishing network connections or unforeseen race conditions. It can scale effortlessly as your app grows. Cloud Firestore allows you to run sophisticated queries against your data. This gives you more flexibility in the way you structure your data and can often mean that you have to do less filtering on the client, which keeps your network calls and data usage more efficient.

Enterprise-grade, scalable NoSQL

Cloud Firestore is a fast and fully managed NoSQL cloud database. It is built to scale and takes advantage of GCP’s powerful infrastructure, with automatic horizontal scaling in and out, in response to your application’s load. Security access controls for data are built in and enable you to handle data validation via a configuration language.

For far too long, managing employee expenses has been a time-consuming process that requires manual data entry and reconciliation to bridge the gap between business bank accounts and ERP systems. In the absence of an integrated workflow, finance teams use multiple systems to manage credit card and cash payments, and finding receipts. In most cases, they also lack real-time visibility into company spending.

The complexity grows exponentially as businesses expand, especially into new regions. Extra administration required to manage new bank accounts, card issuers, and local accounting systems impedes decision making and negatively impacts revenues and growth. Businesses of all sizes struggle with this, but it can be especially challenging for medium to large enterprises.

Payhawk set out to help businesses overcome these challenges when we founded the company in 2018. We combine VISA company cards, reimbursable expenses, and accounts payable into a single product. Our customers can automate manual processes, maximize efficiency, and accelerate business expansion.

Setting up our first cloud cluster in less than a week

To support growth and attract investment we were keen to launch our solution on a scalable, future-proof IT architecture that didn’t require extensive technical support. This is where Google Cloud made a big impression, especially the user interface and documentation which massively reduces the resources required to set up clusters and put them into production.

I’m a CTO, not a DevOps specialist, but in less than a week I was able to set up a secure, reliable operating infrastructure. This enabled us to fast-track our application development and we were able to issue our first card in just eight months. Our Google Cloud partner, Cloud Office also gave us valuable assistance, guiding us through the deployment process and advising on Google Cloud’s extensive range of solutions.

Google Kubernetes Engine (GKE) played a critical role, accelerating the deployment and management of our cloud native applications. We use Cloud SQL as our database while other important tools include Cloud Memorystore, Vision AI, Cloud Storage and Artifact Registry for our wider data storage and application needs. With Firebase we’ve been able to build a notification system for mobile devices.

Another incentive is that most other cloud solutions require add-on services to build and keep your product live. With Google Cloud, all the services that Payhawk needs including logging, metrics, monitoring of resources, and utilization of CPU memory come as standard.

For instance, I was really impressed by Google Cloud’s operations suite, which includes Cloud Logging and Cloud Monitoring. If there are any anomalies in our cloud architecture, we can track and resolve them with minimal disruption to our operations. This also removes the need to invest in an additional observability solution.

Reliability that builds customer trust

Google Cloud also supports Payhawk’s mission to put customers at the center of our organization. Thanks to Google Cloud error reporting and tracking and Google Cloud single sign on, Payhawk’s engineering team can anticipate customer issues and correct them in less than one hour. Trust is everything, and Google Cloud gives us the tools to boost customer satisfaction and build long-term relationships.

As a young business, managing costs is also a priority. The Google for Startups Cloud Program, which includes credits for Google software and tools, enabled us to push the business forward without having to worry about financing our infrastructure, especially in the first year. This gave us breathing room to work through funding, application development, and the onboarding of our first customers.

In addition, Google Cloud gives us confidence that we can grow the business fast. In most months we have seen more than 10% growth — in some cases it’s been 20%. In the first half of 2022, the business doubled in size, but Google Cloud gave us the flexibility to scale our infrastructure, adding storage, memory, and processing power as we onboarded new customers. The pricing model is also generous so that we can grow our revenues while keeping control of operational expenditure.

Since launch we have acquired a valuable mix of customers from startups to large businesses that want to reduce the costs of their expenses programs and increase employee satisfaction. They include ATU, a German automobile servicing company, which has successfully digitized its entire procurement process, and Discordia, a Bulgarian logistics business with 10,000 trucks, which has issued Payhawk cards to all its drivers.

Looking to the future, it’s no exaggeration to say that Google Cloud is a foundation of our business and has given investors confidence in our operations. From a first seeding round of €3 million, early this year we closed a Series B extension of $100 million. This gives us a valuation of $1bn and makes Payhawk the first ever Bulgarian unicorn.

We now operate in 32 countries in Europe and the US, and plan to double our team by the end of the year. It feels like we’ve come a long way since we first started using Google Cloud, and I’m thrilled that we have Google Cloud as a global technology partner supporting our mission to transform expense management and financial operations worldwide.

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.

Like countless other industries, farming is going digital and undergoing big changes—driven by access to more actionable information. The agriculture business can now gather and analyze georeferenced data from satellites, combined with data from IoT sensors in fields, crop rotation and yield histories, weather patterns, seed genotypes and soil composition to help increase the quantity and quality of crops.

This is essential for businesses in the agriculture industry, but it’s also critical to address growing food shortages around the world. 

At S4, we create technology to de-risk crop production. We provide customers seeking agricultural risk management solutions with the tools to make better, data-driven decisions for their crop planning, based on machine learning and proprietary algorithms.

We interpret plant evolution on a global scale with predictive modeling and analytics, and offer super-efficient risk-transferring solutions. Our multi-cloud platform includes a petabyte-scale database, an open source stack, and—after 50 proof-of-concept evaluations—BigQuery for our data warehouse and the Cloud SQL database service to handle OLTP queries to our PostgreSQL database.

These PoCs included, among others, Microsoft Azure Data Lake Analytics, IBM Netezza, Postgres/PostGIS running on IBM bare-metal servers with SATA SSDs and on Google’s Compute Engine with NVMe disks, and on-premises memSQL, CitusData and Yandex ClickHouse. 

Weeding out risk in an uncertain market

According to recent research, climate extreme events like drought, heat waves, and heavy precipitation are responsible for 18-43% of global variation in crop yields for maize, spring wheat, rice, and soybeans. This is a clear trend for other crops as well. Such variation poses risks of food shortages as well as large financial risks to farmers, insurers, and regions dependent on successful crop yields. Also, it creates vast humanitarian difficulties.

Our mission at S4 is to help de-risk crop production by matching the right data with analytics tools so farmers and other participants in the agricultural value chain can plan better, resulting in more reliable food supplies.

In a nutshell, we create indices out of biological assets. These indices measure yield losses on crops that are caused by the effects of weather and other factors, which are then used as underlying assets for products, such as swap/derivative contracts and parametric insurance policies, to transfer risk to the financial markets.

We enable insurers and lenders to buy and sell agricultural risks through the futures market. Also, our other products help farmers and seed and fertilizer companies provide customized genotype recommendations and fertilization requirements. This helps to optimize planting by geography, resources, and crop species, monitor phenological, pests and humidity evolution throughout the crop season, and estimate yields.

Local communities benefit from S4’s technology, as the ability to manage weather risks allows farmers to stabilize their cash flows, invest more to produce more with fewer risks, and develop in a more sustainable manner.

Growing data sources, reducing costs, accelerating performance

With the volume of diverse data sources and analytical complexity both growing at a very fast pace, we decided that using a major cloud services provider with a broad roadmap and global partnerships would be beneficial to S4’s future evolution.

At the same time, we wanted to bring our services to users faster and cut costs by consolidating our on-premises technology stack. When we started evaluating providers, our leading criteria included a powerful geospatial database and data analytics tools along with excellent support, all at a competitive price. GCP prevailed in nearly all criteria categories among the 50 companies we measured. 

Our previous platform architecture included a hybrid relational database that used Compute Engine for virtual machines and Cloud Storage for database backup. The RDBMS was slow. Maintaining our own data warehouse was complex and expensive.

We wanted to use machine learning and neural networks, but couldn’t do so easily and affordably. The complexity of that system meant that products or services requiring small changes or additions to the data model translated to expensive expansions of infrastructure or project time.

Also, agronomical or product teams couldn’t test these changes by themselves, always requiring the intervention on no small part of the IT team, which led to further delays.

We added GCP services like BigQuery as S4’s cloud data warehouse and use BigQuery GIS for geospatial analysis, Cloud Dataflow for simplified stream and batch data processing, and Cloud SQL for queries to the S4 database platform, which have all made a huge impact on our services and bottom line.

Database and analytics costs have decreased by 40% and customers are receiving our analytical results 25% faster. In addition, we’ve eliminated the time-consuming downloading of images, reducing storage and processing costs by 80%, because we no longer need expensive tools licenses, and have greatly reduced classification processing times.

Our customers working in the agriculture industry are also benefiting from this infrastructure change. They are now able to speed up their data analytics using our GCP-based platform.

“S4 products and technologies unlock the full potential of satellite imagery for crop prescriptions, monitoring and yield estimates,” says Nicolás Loria, Manager of Marketing Services, Southern Cone, Corteva Agriscience.

“We’ve worked with S4 for the last three (and starting year number four) crop seasons as its team capabilities, data integration capacities, and analytics insights have allowed Corteva to perform an entire new solution. Thanks to S4’s customized 360° approach, fast response and delivery times, we have safely outsourced our remote crop analytic technical needs.”

Also, this new architecture has allowed us to scale our models and databases with almost no limits, at a fraction of the cost vs. the previous models.

We’ve saved a lot of time on executing processes and reduced work needed by our internal teams to do certain tasks, like preparing images, converting them, validating results, and more. Using Google Earth Engine has decreased the execution time of daily tasks anywhere from 50% to 90% of the previous time, going from an average time of 30 minutes to between four and 15 minutes, depending on the task.

In addition to saving money and time, we are able to focus on innovation with the GCP performance and features we’re using. We’re able to seamlessly add satellite data to analytics using both public datasets and our own private data, and deliver GIS data management, analytics, crop classification and monitoring in real time.

We can do semi-automatic crop classification and classification using spectral signatures with Google Earth Engine. Later this year, we’ll be using neural networks for pattern recognition and machine learning in new applications to improve crop yields and fine-tune risk models. And using GCP and Google Earth Engine infrastructure means we can run models for customers in South America and around the world, since Google Earth Engine has global satellite imagery available. 

We’ve heard from our customer Indigo Argentina that they’re able to bring customers data insights faster.

“We are working with S4 in the development of two different applications for satellite crop monitoring and yield assessment,” says Carlos Becco, CEO, Indigo Argentina. “S4’s technology allowed us to manage and analyze multiple sources and layers of information in real time, letting us uncover valuable insights in Indigo’s own microbiome technologies, and at a very competitive cost.” 

Analytical products and app development thrive with GCP

With GCP, we are updating and improving algorithms that we built manually with machine learning processes to develop drought indices for upcoming crop seasons. Algorithms can recognize specific phases of crop phenology (e.g., bud burst, flowering, fruiting, leaf fall) and correlate them with photosynthetic activity, light, water, temperature, radiation, and plant genetics factors. Other analytical products like crop monitoring, pre-planting recommendations, financial scoring, and yield estimation can now do a lot more for users by offering multiple layers and datasets, faster image processing, and real-time access via APIs.

We also replaced our bare-metal S4 app deployment with the App Engine serverless application platform. It provides tighter integration between the S4 platform and our BigQuery data warehouse for integration with marketplaces and third-party solutions.

We get all of these Google Cloud features with all the benefits of managed cloud services, from multiversioning and security to automatic backups and high availability.

At S4, we trust technology to decode plant growth and help protect farmers and their communities from climate change. With growing food shortages due to increasing populations and intensifying weather, data and analytics can have a huge impact in lowering financial risks and improving agricultural yields. It’s one sector where cloud, database, analytics, and other technologies are combining to improve business outcomes and affect the lives of billions of people. Learn more about S4’s work and learn more about data analytics on Google Cloud.