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Case Study

Omega Point Finds mLab's Database-as-a-Service to be a Sound Investment

A startup offering investment portfolio managers rich quantitative data to guide their decision-making, Omega Point needed to handle vast amounts of data without compromising product development. To do so, the company's founders enlisted mLab as an easy-to-use solution for hosted and managed MongoDB databases.

Highlights
  • Omega Point provides users with data on over 40,000 public equities and over 650 key market insights for each stock.
  • With Omega Point determined to give users a fast and intuitive interface, mLab's database platform ensures the company's client-facing web application is highly performant and available.
  • Omega Point maintains 99.95% uptime while operating with zero in-house staff devoted to DevOps. The company has been able to fully focus its resources on product development by relying on PaaS providers including mLab's managed service.
Customer Profile

Omega Point brings advanced quantitative investing to fundamental-style asset managers, funds of funds, and endowments who manage over 85% of the world's assets. The company provides insightful market trend data on more than 40,000 securities.

The Challenge

To help investment portfolio managers take advantage of market trends, Omega Point sought to develop a platform that makes quantitative analysis accessible through modern cloud technologies.

Omega Point was founded in 2013 out of a drive to democratize the quantitative capabilities used within proprietary systems at the most successful hedge funds in the world, and to build a more modern (cloud-based) software platform to deliver them. These systems function by taking and analyzing data, and using the insights derived from that data to make buy / sell decisions in the financial marketplace.

Omega Point's founders began by identifying what data could be leveraged to maximize value for portfolio managers and similar investment professionals. These managers - overseeing assets ranging from the tens of millions and to billions of dollars - need efficient systems to manage and understand what's happening in their portfolios. Omega Point found that the best-performing hedge funds are those with the greatest ability to quickly and easily identify trends in the market (using data), which they then apply to their trading strategy.

The process that Omega Point developed begins with about four terabytes of raw data on securities, which is put through big data processing and then pulled into a suite of applications. Omega Point's goal is to provide investment managers with the best interface it can - delivering its customers key insights so that they can use the software to instantly take advantage of market trends.

Because Omega Point is pulling in large amounts of data - and constantly expanding its platform to include valuable new metrics - it needed a system designed to grow and handle unstructured data with ease. This made the decision to seek out a NoSQL solution an easy one, as a non-relational database would best fit Omega Point's constantly evolving schema; the company currently tracks 40,000+ securities and 650 metrics (updated daily) for each stock. The team chose MongoDB as the database technology because it could handle the technical requirements and integrated well with the JavaScript development stack.

With the database technology now decided, Omega Point sought a provider that could deliver MongoDB with more simplicity and cost-efficiency than building out an in-house team.

Solution

Realizing how the capabilities of database and IT infrastructure service providers had improved drastically in recent years, Omega Point's CTO turned to a DBaaS strategy - and to mLab.

At his ventures before co-founding Omega Point in 2009, CTO Eran Cedar purposely did not use as-a-Service database and infrastructure providers. They had proven inadequate for building a business, and Cedar had ended up hiring talented engineers for his DevOps teams (although at a considerably higher cost). However, while starting Omega Point, he had seen how cloud services had evolved and could offer the needed expertise, optimization, and application of best practices more effectively and cheaply than an in-house team.

While evaluating managed MongoDB providers, mLab emerged as the service with simple, transparent pricing and the strongest reputation for performance and helpful support. With mLab, Omega Point was able to get all of its databases up and running on day one.

Since the initial implementation, mLab has continued to deliver reliable service as Omega Point has grown. Omega Point cites mLab's Slow Query Analyzer and highly responsive support as being particularly critical to the successful engagement.

I don't want to experiment with the database - I just want it to work. I want a technology provider that knows the technology well, and has a strong reputation amongst its customers. mLab checks all those boxes. When we first compared providers, there was a lot of praise online about how mLab had some of the best expertise in MongoDB out there, and that has certainly proven to be the case. The platform is easy to use, and offers the features and expert support to address issues quickly and in the best way.

Eran Cedar CTO and co-founder, Omega Point

Benefits

mLab has provided Omega Point with a seamless database experience throughout the company's continued growth.

For Omega Point, working with mLab has been a smooth engagement from the very beginning. It has found that, with mLab, the database is something that it never really has cause to think about. Even when Omega Point underwent a database migration with mLab to increase capacity, the company found it to be a non-event because the process was so frictionless and invisible to users.

And, in keeping costs down, Omega Point has not needed to hire an internal team to manage their infrastructure, instead focusing resources solely on product development. The current engineering team includes product-oriented data scientists, data engineers, application engineers, and staff focused on product design - but zero dedicated DevOps or database administrators.

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