Small, but powerful: groundbreaking startups in the world of Big Data

Small, but powerful: groundbreaking startups in the world of Big Data
Small, but powerful: groundbreaking startups in the world of Big Data


The global market for Big Data could exceed 46 billion dollars in 2018, with an annual growth of 25% from 2013 to 2018. Clearly, it’s a business opportunity in the world of technology, for both entrepreneurs and developers. The industry is going through continuous movements, with the birth and growth of startups in fields such as machine learning, deep learning, visualization, processing, storage and analysis of large volumes of data… it’s a ruthless race for private funding and for consolidating a strong market position. This is a list of some of the companies with the best present and future:


This Californian startup created by ex-employees of Facebook is one of the great revelations in the world of Big Data. What do they do? The company managed by Ann Johnson (CEO), Bobby Johnson (CTO) and software engineer Lior Abraham provides businesses a data analysis solution which focuses on information flows over time, displayed with a simple visualization. Both the storage engine and the user interface have been developed by Interana, although they profit of several years of work at Mark Zuckerberg’s social network. The idea is that anyone interested in data, technical or not, can extract useful information.

Interana has designed software that allows to manage large volumes of data that would be infeasible to run in a cloud service. The platform focuses on the analysis of events over time and the elaboration of funnels to determine the path followed by the user to that event.

The market believes blindly in its enormous potential. In fact, at the end of January 2015 Interana closed a funding round of 20 million dollars.

New Relic

This startup has a system that monitors in the cloud and in real-time the response of machines to apps, both in Android and iOS operating systems, and all types of programming languages (Java, PHO, Ruby, .NET, Python, etc.). New Relic allows to add the platform’s agent to any platform/server and start getting insights about response or execution time, error messages, authentication errors, memory usage, user statistics… In addition, you can set different thresholds for each of these insights to generate automated alerts. New Relic’s platform receives the data and generates graphics, easy to understand and from which to draw interesting conclusions to optimize applications and servers. The founder and CEO of the company, Lew Cime, was a software engineer at Apple.



When Google Ventures is funding a project, it’s likely to be something quite promising; and if it’s part of a funding round of 16.1 million dollars, even more. Tamr is a Massachusetts-based startup founded by an MIT professor and data guru named Michael Stonebraker and an entrepreneur and researcher named Andy Palmer, who previously was involved in the birth of companies like Vertica and VoltDB.

Tamr offers simple and scalable solutions to automatically convert, validate and package data of for example large clinical studies. It does so applying machine learning. Today, any pharmaceutical needs to invest time and money in finding, extracting and archiving data from different sources, and then carry out the whole process of adaptation to legal standards. Tamr solves that problem.



This startup uses machine learning to make medical diagnoses in a fast, accurate and accessible way. Enlitic solutions allow any doctor to seamlessly access medical data, including images, notes or laboratory tests.

How do they do it? They use deep learning algorithms, which combined with documents from leading US hospitals and medical device manufacturers can generate a huge structured medical database of instant access. This solution can become a very powerful tool to help diagnose diseases. Today, doctors face difficulties when trying to manage effectively all this wealth of data, as they don’t have tools able to detect patterns that lead to early diagnoses. Enlitic develops software that helps physicians manage data and speed up diagnoses.


MetaMind is a startup that provides Artificial Intelligence solutions to companies through deep learning. In 2014 they completed a round of funding of 8 million dollars with Khosla Ventures and CEO Marc Benioff. This startup has one of the best solutions for image and text recognition currently available in the deep learning market. The best of MetaMind’s solutions is that you don’t need to be a programmer or have a cloud service for your data.

An example is its tool for classifying tweets, which any user can try in the company’s demo page. The tool recognizes the text (username or hashtag on Twitter), searches in the social network and classifies the tweets in three different groups: positive, negative or neutral comment. Actually, the tool makes a double process of natural language recognition: first it understands your request, and then it reads the tweets and understands if they are negative or positive.


ElasticSearch has made a lot of noise with the enormous potential of its open source tool for searching large volumes of data and the analysis of that information through simple visualizations. The startup currently has three basic products: Elasticsearch, Logstash and Kibana. Among the three companies they total more than 8 million downloads.

Elasticsearch is the company’s open source real-time search engine, designed for environments where high reliability and scalability are required and for clients who work with various programming languages. Logstash is perhaps the most popular open source log management tool in the market. It handles log data and events in real time and stores them for processing in a format simple to read such as JSON. The third product of the startup is Kibana, a data visualization solution in panels easy to develop and understand by someone without technical knowledge. These panels can be shared and are modified in real time.


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