Customer Story

Density

Density helps its customers with substantial real estate portfolios, from Fortune 100 to high-growth tech companies, improve employee experience and reduce carbon footprint. Density’s platform can reveal if employees are choosing focus space or collaborative space, which floors are the most popular (and why), and how an office’s occupancy rate compares to others in a portfolio or against industry benchmarks.

Density built an entire time-series database using stored procedures and vanilla PostgreSQL. It was difficult to query the data and enable customers to slice it into multiple dimensions. It was more complex to operate large query plans with vanilla PostgreSQL and trim them to something predictable, reasonable, and performant at relatively low latencies. Development was slow, and they had to manage decision logic and complexity around time zone handling and bucketing themselves.

Timescale’s flexibility and ability to handle large volumes of data reduced the manual effort and slow queries with vanilla PostgreSQL. The time_bucket function returns buckets of time ranges according to requested window sites and handles difficult elements, such as time zones or daylight savings. Density found that Timescale is dynamic—they can slice and dice queries in a more or less arbitrary number of ways. Timescale’s flexibility and ability to partition and create hypertables to access data back in time quickly is a winning combination for their use case.

When Density began to use the platform, Timescale made development significantly faster. Continuous aggregates also enabled them to roll up multiple resolutions of sensor account data, people count data, and make it available more efficiently with little to no effort related to the code they had to write to deliver those efficiencies.