A Schemaless Database for Lease Financing

LeaseSolution Develops LS2X for Lease Portfolio Solutions using RavenDB

The market for equipment and software financing will surpass $1.25 trillion by 2021.

At any point, a company can hold thousands of leases making up a non-trivial portion of their incoming sales. Maintaining these leases can be the difference between a quarter of cash flow or three months of burning money.

LeaseSolution develops LS2X, software for managing the leases companies issue in selling large orders. Clients like Samsung and Computacatcher use it to track leases which can be anything from a 6-month agreement for $1,000 to a multi-year contract for over half a million dollars.

LS2X tracks all the details of each lease. It determines when the next payment is due and automatically sends the invoice. It aggregates all payments made, updates the balance outstanding, and even calculates in real-time how much of it is interest and how much is principal.

They track aggregates on a massive scale.

A report can be generated in a flash containing each client, how much they paid for all leases, how much they owe, how many leases they have, and how many were issued in the current business period. They can break it out over weeks, months, quarters, or years.

One report contained 1,100 customers, each with four aggregated totals. Their database is tasked with calculating, updating, and maintaining these aggregates at all times, delivering them to the client immediately upon request.

A Fully Schemaless Document Database

They first tried SQL Server. When that failed, they attempted MongoDB. Both proved inadequate for the same reason: too much schema.

One of the main features LS2X offers clients is the ability to tailor the information they need to their specific payment and collection systems. Certain fields are required to be kept out of some clients. Other clients needed different data types. Specific clients needed unique pieces of data that required breaking the mold of the basic templates.

To achieve this level of capacity for the client, they need a practical, fully schemaless, document database.

RavenDB enables LeaseSolution to give each customer exactly what they need.

A Database to Love

Since 2015, RavenDB has been the backend for LeaseSolution, providing their data store and calculations for over 4,000 aggregates clients request in real-time.

They love RavenDB for its ease of use in C#. They also love RavenDB for its ability to maintain running aggregates. When an aggregate is computed for the first time, it is done the old-fashioned way – calculating all the values and turning them into a total.

Once that’s done, all new data updates will also update the aggregates. The aggregates are kept in memory and updated for every new value that impacts the aggregate.

When a user asks for the aggregate again, it takes 90% less time to serve the request. Clients will call up figures like total leases for March 2018 or current obligations for 2021. They will do it every day. Using RavenDB, the reports generate faster, especially when you have one made up of hundreds of aggregates, like an accounts receivable list of each client and how much they owe the company.

Map-Reduce is part of RavenDB, just like full-text search. Clients need to search on products, specific leases, and leases often. RavenDB’s full-text search enables developers to make the feature available straight from their database.

Scaling Out Your Database

The post-recession 2021 economy has taken off like a rocket. Where purchases of machinery, software and equipment stalled, we are now making up for the lost time. Add in the massive qualitative easing, and you have a tsunami of new leases issued to underwrite the next economic expansion.

Using RavenDB Cloud, our Managed DBaaS solution, LeaseSolution can scale out their database rapidly and efficiently to meet growing demand.

As retail continues its upward flight, RavenDB is right there, ready to spread its wings.

See for yourself! Take a live one-on-one demo of RavenDB to experience first-hand the advantages of modeling data the modern way.