Since VerdictDB is an open-sourced project hosted on GitHub, we are unable to know exactly who or what companies have tried or actively using.
However, we have interacted heavily with the following companies to help them deploy VerdictDB in their production environments.
Making data-driven decisions based on its sales transaction data
is crucial for Walmart's successful business operations.
Unfortunately, due to its scale of operations, the volume of data
Walmart collects is tremendous and ever-growing.
Even with today's commercial distributed stores and compute engines,
the latencies of analytical queries easily exceeded 10-20 mins, significantly
hampering the productivity of its data analysts.
To reduce these long query latencies and improve their productivity,
the data analysts use VerdictDB on top of their existing data analytics
engines without making any modifications.
VerdictDB has successfully reduced the latencies of their large-scale analytical queries
down to a few seconds.
Learn more here.
is a leading company in location data intelligence and real-time consumer engagement.
LOCALLY is interested in building/offering a web-based platform where its customers can
interact (or play) with its massive amount of location data capturing people's
In building such a web platform, the essential part is achieving real-time responses
to the customers' interactions.
For example, if a customer wants to learn how many people are within a certain (arbitrary) area,
the web platform must be able to obtain the number within a few seconds. In this way, the customer
can be more engaged with LOCALLY's platform and use more of its premium services.
In offering these near real-time responses, today's distributed compute engines
(e.g., Amazon Redshift, Facebook Presto) were expensive and still not fast enough.
To solve this problem, LOCALLY uses VerdictDB, which can compute
the answers to big queries only within a few seconds using a small cluster (thus, affordable).