Evaluating New Technologies with StackShare.io

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By: Julia Lien – ODSC data science team contributor


To stay up-to-date with current technologies, some follow blogs while others go to Data Science Conferences. The upcoming ODSC East Conference will include tutorials and workshops that will keep you updated on the latest and greatest tools. In between conferences you’re likely to google your way to the coolest new widgets, skimming through a mountain of documents, articles, and user reviews until your aptly swayed.

Enter StackShare.io1.

StackShare is a website that curates and crowdsources software tools and cloud infrastructure services, displays them in a pleasant UI, and lets us in on who’s using what. There are several ways to browse – we can see what tools or stacks are trending, look up a company’s tech stack, discover tools/services by category, and browse featured blog posts.

Browse Tools & Services
StackShare has a great taxonomy for grouping tech tools and services by functions. Broadly, tools are separated into Application and Data, Utilities, DevOps, and Business Tools categories with finer groupings within each. The Data Stores2, Libraries3, and Application Utilities4 groups (which includes subgroups such as Web Scraping API, Machine Learning as a Service, NLP/Sentiment Analysis) are of particular interest to data scientists and engineers.

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Each tool and service in StackShare also has its own page where users can leave one-liners on what they like about the tool, contribute more in-depth reviews, see what companies are using the tool, and check out similar tools and services. You can also create side-by-side comparisons of these metrics on any combination of tools, like for this age-old R vs Python debate.5

This view is most helpful if you are looking to find tools for a specific use case or just discover new tools in general.

Browse Stacks
The Stacks page showcases various startups and their tech stacks. Some company stacks have been verified by at least one person from the company, and others at least contain article references that show how they know the company is using a certain tech. Although the level of detail and frequency of updates varies for each company, the fact that you can casually browse what analytic-intensive companies like Airbnb, Spotify, and Netflix are using in the same site is pretty exciting. Companies can also contribute more details on how they’re using each tool or what they think of each tool, though most companies don’t have that filled out.

This view is most helpful if you’re envious of a company’s processing power and want to know what sorcery is happening behind the scene.

Browse Posts
The Featured Posts page showcases guest blog posts by different companies alongside their stacks. In each post, tech wizards of startups will describe the nature of his/her company’s work (i.e. what kind of processing/storing/speed their tech stack will need to handle), tech stacks they have tried, their current tech stack, challenges they’ve faced, and lessons they’ve learned along the way. These are extremely helpful, especially if you have similar tech needs to the company featured or if you are trying to evaluate some of the same technologies.

This view is helpful if you’re looking to learn from other people’s experience, and would like more in-depth reviews of stacks. You’d find these most interesting if you care about DevOp-y things like workflows, testing, deployment, scaling, and processing.

Be Part of the Community
StackShare is a great resource for developers. It’s currently lacking in the Data Science Tools department 6, most likely due to the current user base of StackShare, but we can change that if we all jump in and start adding more data science tools and user reviews to their tool base.