Startups Using Elasticsearch in Boston
Via their job posts and information submitted by startups themselves, these are the Boston Elasticsearch startups we've found.
Interested in other technologies? Browse or search all of the built-in-boston tech stacks we've curated.
Product content management system to “make it easy for manufacturers, distributors, and retailers to exchange high-quality content that drives online results”.
Recruiting software for automatic, role-specific resume review & follow-up candidate questions.
Tech Stack Highlights
Postgres & Redis – All this is backed up by RDS instances in AWS running PostgresDB. We heavily use Redis and SOLR for data caching and queue management.
Flask/Python – The rest of our apps and services – Email systems, data analysis, internal tools – all run in Python based Flask/Flask-Restless environments.
ELK – Our logging system is run as an Elasticsearch-Logstash-Kibana stack utilizing Filebeat and Logspout for streaming the log output. From this stack we’ve also created a comprehensive Technical SEO Dashboard where we can monitor crawlers and their activity and measure the cause & effect on new site features.
DevOps – Our apps are deployed using Docker Swarm orchestration via Ansible scripts for independence from specific cloud providers. We’ve built a structure with Docker in a Blue/Green deployment methodology so there is zero downtime when releasing code updates. The system is front ended with Jenkins-CI for automated execution of Unit/Integration/Acceptance test suites.
Podcast discovery and listening platform. Building “the new radios of our time.”
Software tool suite for English-as-a-second-language teachers.
Tech Stack Highlights
ASP.NET MVC/Web API – Using these enterprise-grade frameworks and Visual Studio enables us to focus on delivering value to our customers through new web-based products and features. Documentation and IDE support for .NET and C# is incredibly rich. We also depend heavily upon continuous integration (CI), one-click builds, and Selenium automation tests to build in quality from the start.
Elasticsearch – We’re using Elasticsearch as our search platform to enable educators to construct and perform complex queries to identify and visualize data about students, such as those that might need extra attention or are at risk. Student data, especially for English Language Learners (ELLs), is incredibly nuanced and is comprised of many different properties. Elasticsearch helps us scale to support the fast searching of multiple data sets from each of our school district customers.
Python – We find that it’s one of the best technologies for data wrangling, especially when using packages such as pandas. Whether it is manipulating large datasets in MongoDB via map-reduce functions, or transforming data files containing important student data, Python is our tool of choice in this area.
Octopus Deploy – We use Octopus Deploy for our deployment automation platform. It holds a near and dear place in our hearts because it provides first-class support for Windows/.NET and is extensible, open and reliable. And it’s from Australia!