If you’re in the process of job hunting, chances are you checked out Glassdoor.com, the go-to website for workplace transparency. Glassdoor offers valuable career-related data to the job seekers through anonymous reviews by both former and current employees as well as information about salaries and benefits. With more than 59 million unique monthly web visitors, Glassdoor is a reliable source of information that today’s workforce can trust.

Now, with the acquisition of Fishbowl, Glassdoor is taking workplace transparency to the next level. Fishbowl, a professional social network, enables anonymous conversations about workplaces, providing authentic advice from verified employees who work at today’s leading companies.

“The acquisition of Fishbowl has made Glassdoor an even more powerful tool for workers,” reveals Julio Viera, Head of Engineering at Fishbowl. “With Fishbowl, job seekers and workers can now gain a more authentic perspective of companies, including advice on where to apply, how to succeed in interviews, and insights into peer salaries. This increased transparency through workplace conversations will lead to a more comprehensive understanding of company culture and empower professionals to make more informed decisions about their careers,” Viera added.

Fishbowl isn’t just revolutionizing the workplace for professionals, it’s also collecting valuable data that companies will be able to use to track trends and find out the true, unbiased sentiment of its workforce. MongoDB has been a supportive partner since day one, helping people to search for relevant content and categorizing content posted on the site.

Fishbowl was founded in 2016 and acquired by Glassdoor in 2021, and just a little over one year later, it already has more than one million active users, with 23 million comments across four million posts. As the website’s growth relies on users searching for relevant companies and content, the right infrastructure was crucial for a successful launch.

The Fishbowl team needed a database with the ability to scale in line with growth. It also needed to fit seamlessly into its AWS environment and be easy for the development team to work with.

“Our vision is for Fishbowl to be the go-to place for conversations around careers in years to come. We’re gradually integrating it with Glassdoor, so users of the mobile apps are already seeing Fishbowl content when browsing Glassdoor,” explains Viera. “We want to take that experience to the next level, and show job offers on Fishbowl when someone talks about switching jobs, creating a fully integrated user experience.”

To achieve this and reach its goal of monetizing data and analytics for businesses, finding the perfect solution to meet Fishbowl’s needs was essential, leaving no margin for error.

The company implemented Atlas, MongoDB’s developer data platform, on AWS. “MongoDB fits our data structure very well and makes it easy to scale and monitor our environment, which will save us money in the future,” reveals Viera.

Initially, the team used Elasticsearch for search functionality. However, the Fishbowl team encountered issues with increasing complexity as they scaled. In order to use Elasticsearch, they needed to set up a data sync to push their data from Atlas to Elasticsearch, which led to increased architectural complexity and operational overhead to keep the data in sync between the two systems. When issues occurred with the sync, users experienced inconsistent search results. It also led to instances where content was taken down through content moderation processes but might still be shown as a stale result to site users.

The team quickly decided to replace the solution with MongoDB Atlas Search. Because Atlas Search is collocated on Atlas clusters, it eliminates the need to set up and maintain a sync mechanism to push data to a bolt-on search engine. Moving to Atlas Search enhanced search reliability and allowed the team to focus on delivering value to users.

“The time we spent redoing queries on Atlas was less than we were spending troubleshooting the old solution. The transformation went smoothly, and we’ve eliminated the issues we were having around indexing. We can do tasks like replicating data sets or scaling up and down in a matter of clicks,” comments Viera.

Categorizing content and making it discoverable for users is an important process at Fishbowl. When the team adds a new category, the entire library of content needs to be scanned and classified for indexing. With Atlas Search, the team can run a query, analyze the results to check that data is accurate, and reindex content in 5-10 minutes, a process that previously took days to complete.

“Atlas Search gives our engineering team significantly more time back compared to the previous search engine. We can focus on more satisfying tasks and handle changes faster,” says Viera.

Additionally, features within Search such as “fuzzy search” are proving particularly valuable to help users find the right information even if the search term includes a typo.

And as the platform continues to mature, the team plans to use MongoDB to support more advanced functionality, such as personalizing content in the news feed each time a user logs in. This means users won’t be overwhelmed with hundreds of pages of content and can enjoy a more satisfying experience.

Julio Viera, Head of Engineering at Fishbowl

With Atlas, the team at Fishbowl has a high-performing, low-maintenance database with powerful search capabilities. “The built-in capabilities of MongoDB are mind-blowing. While there are other solutions designed to optimize processes behind the scenes, that’s embedded in MongoDB’s DNA and all the additional features are built on top. It’s a very reliable platform that comes with minimum operational overhead,” comments Viera.

He also praised the end-to-end control that MongoDB unlocks, which makes it simple to identify and iron out any issues with the solution.

Julio Viera, Head of Engineering at Fishbowl

As Glassdoor and Fishbowl strive towards growth goals, Atlas is able to provide the scalability to handle higher volumes of traffic and searches with no impact on performance.

"Atlas not only allows us to manage the MongoDB cluster efficiently, but it also comes with built-in tools such as a profiler, performance advisor, charts to analyze data patterns, system health dashboards, and many others. All these are critical to ensure we use MongoDB as efficiently as possible, making it a very cost-effective solution," shared Ilya Starostin, Sr. Engineering Manager at Fishbowl.

Ilya Starostin, Sr. Engineering Manager at Fishbowl

Fishbowl is in the business of providing greater transparency to users and infusing the workplace with more authenticity. For users, being able to quickly find the right information or contacts could be the difference between having the confidence to ask for a pay raise or knowing how to dress to impress at the interview.

“Being able to deliver a great user experience means we can turn people into lifelong fans. We want to support them throughout their careers, and we are able to give them the outstanding experience they deserve thanks to MongoDB,” concludes Viera.

Julio Viera, Head of Engineering at Fishbowl