By Sachin Smotra
It’s been a year since Couchbase Analytics was launched and I have spoken to enterprises — both large and small — across multiple verticals: retail, hospitality, manufacturing, healthcare, and sports/entertainment. Of late, I repeatedly get asked how are Couchbase customers using the latest addition to the Couchbase data platform today? So I’m going to give a few of my favorite examples of the very innovative ways our customers are using Couchbase Analytics. But first, let me tell you a little bit about the solution.
First off, I just need to clarify that Couchbase Analytics is not a data lake! A typical enterprise might have a data warehouse, a data lake, and hybrid database. The data warehouse is designed to handle massive amounts of data, but with a predefined schema. As a result, any process writing to the data warehouse needs to understand the schema to be able to write to it.
The data lake, which is now being called the kitchen sink of enterprise data, relaxes the need for the upfront definition of a schema. As a result, any process can write to the lake without any rigid schema requirements. However, data lakes do require a schema on read, which means that any consumer of data stored in the lake would need to define a schema.
For operational data being generated by applications, a hybrid database provides the ability to analyze data as it comes in with a heavy transactional workload, but without impacting the transaction throughput or latency.
Couchbase Analytics is a hybrid NoSQL database that enables rapid time to insight for operational data.
Use Cases
Finally, the pudding! As in, the proof is in the pudding. Here are four real-world use cases that also happen to be world class examples leveraging data to obtain a competitive advantage.
- A top cruise line is revolutionizing the passenger experience by using analytics to add a personal touch from ship to shore. Even when they’re at sea with spotty connectivity, the cruise ships are able to collect, process, and analyze data from onboard sensors and passenger medallions. Couchbase enables the cruise line to operationalize the analytics in real time without the heavy lifting of data lakes, data warehouses, or ETL processes.
- A leading retailer uses real-time shopping cart analysis during Black Friday and summer sales to eliminate duplicate items in carts, identify top-selling items, and conduct other data exploration directly on JSON data. The ability to process heavy transactional data in real time without impacting throughput, latency, or the online shopping experience was this customer’s most critical requirement.
- A prominent healthcare provider uses Couchbase Analytics to eliminate the need for an ETL pipeline. Their previous analytics infrastructure required a complex pipeline with an elaborate schema that had to be redesigned every time they needed a new report. With Couchbase, they now analyze large amounts of JSON data in its original state to drive better outcomes for both patients and providers.
- A Major League Baseball team uses Couchbase Analytics to modernize the fan experience. For instance, they optimize food cart placement in real time based on stadium occupancy. As fans scan their tickets to get seated, concessions personnel use a live seat map to place the food carts closer to the fans so they can get their food and drinks faster.
As you can see, these are four very different examples from four different industries that demonstrate some great forward thinking from an end user perspective. Data lakes, data warehouses, and hybrid databases are posing a different set of challenges for enterprises, and I’ve shared my perspective in this Q&A on odbms.org.
Additional reading: Comparing Two SQL-Based Approaches for Querying JSON: SQL++ and SQL:2016, by Don Chamberlin, co-designer of the original SQL.
Sachin Smotra’s career spans more than 15 years building software products across various domains including Java Enterprise software, DRM Solutions for mobile games and web conferencing. He previously served as Director of Product Management at Couchbase, where he was responsible for Couchbase Analytics, Mobile & IoT product lines.
