The 10 Coolest Big Data Startups Of 2017
Big Doings In Big Data
The big data technology arena continues to rapidly change as the demands on data management and business analytics systems continue to expand.
Today's big data systems are more automated, more real time and more mission critical. Businesses are increasingly relying on them to integrate and analyze data that's scattered across many locations – including on-premises and in the cloud. And less of that data is traditional structured data while the volume of unstructured data, machine data, streaming data and Internet of Things data continues to grow.
An ever-changing number of technology startups are developing the leading-edge software and systems to meet these big data demands. Here are 10 cool startups in the big data realm that caught our attention in 2017.
Get more from CRN's 2017 tech retrospect.
CEO: Jeremy Achin
DataRobot develops an automated machine-learning platform that captures the knowledge, experience and best practices of data scientists and uses that information to build and deploy predictive models much more quickly than has been possible. With those models, analysts can uncover hidden opportunities and predict outcomes from huge volumes of data.
Boston-based DataRobot, founded in 2012, was already gaining attention when in May it acquired Nutonian, another data science software development technology company that focused on time-series analysis modeling.
DataRobot snagged $54 million in Series C financing in March and has aggressively invested in its global partner ecosystem. In September the company hired Alteryx executive Seann Gardiner as its executive vice president of business development.
CEO: Ian Swanson
Data scientists are in short supply and making the best use of their talents is a major goal for many data-driven companies.
DataScience offers the DataScience Cloud, an enterprise platform that helps businesses maximize the value of their data science teams by automating engineering tasks, streamlining workflows, and providing tools, libraries and built-in expertise.
DataScience was founded in 2014 and is based in Culver City, Calif. In October the company partnered with big data platform vendor MapR Technologies to create a joint solution that runs data science experiments on the MapR system to power a new generation of data-driven applications.
CEO: Doron Alter
Endor has developed a predictive analytics platform that allows business users to ask any question, such as "Who is likely to try this new product?" and "Where should we open our next store?" and get an answer in minutes.
The company based its proprietary technology on "social physics" research from the Massachusetts Institute of Technology. While machine learning may be good at predicting, say, when a critical piece of equipment will fail, social physics uses big data analysis and the mathematical laws of biology to understand the behavior of human crowds.
Endor (yes, it has the same name as the planet in "Star Wars") was founded in 2014 and is based in Tel Aviv, Israel. This year Gartner named the company a cool vendor in business analytics and the World Economic Forum named it a technology pioneer.
Founder: Koichi Fujikawa
Amazon Web Services' Redshift cloud data warehouse system is becoming a popular alternative to building complex and expensive on-premises data warehouses. But there's still the challenge of getting data from a company's operational database into Redshift.
FlyData has developed a simple, automated data integration system for setting up a Redshift cluster and replicating data in MySQL databases to Redshift. The company's products include FlyData Autoload and FlyData Sync.
While the Palo Alto, Calif.-based company has been around since 2011, it raised $4 million in Series A funding just this September.
CEO: Tanel Poder
Gluent's mission is to "liberate" data from the confines of proprietary data silos and make it accessible through new, distributed big data systems.
Gluent develops data virtualization technology that makes possible what the Dallas-based startup calls "hybrid data" computing. The Gluent Data Platform offloads data from traditional relational database systems to Hadoop, while still providing access to that data.
The vendor's system creates a way for businesses to leverage the flexibility and scalability of cloud-based or on-premises Hadoop clusters while boosting query performance and reducing storage-area network and relational database license costs, according to the company.
Founded in late 2014, Dallas-based Gluent was recognized as a Gartner "cool vendor" in data management and took second place in the Strata + Hadoop World Startup Showcase in March.
CEO: Osama Elkady
Incorta's mission is to replace traditional data warehouse systems and ETL (extract, transform and load) tools with its data platform for real-time analytics and operational reporting.
Incorta's software uses what the company calls a "Direct Data Mapping" engine that executes complex data joins with real-time aggregations of huge volumes of data.
Founded in 2013, San Mateo, Calif.-based Incorta raised $15 million in September in Series B funding led by Kleiner Perkins. That followed a $10 million Series A round in March that included funding from GV (formerly Google Ventures).
CEO: Evan Kaplan
InfluxData has developed a stack of open-source technologies that together address the problem of managing the continuous flow of time-series data from Internet of Things networks and other systems.
The InfluxData platform offers a range of tools and services, including the InfluxDB time-series database, for real-time processing of time-series data in such areas as Internet of Things, DevOps monitoring and real-time analytics.
San Francisco-based InfluxData, founded in 2012, has raised nearly $25 million in three rounds of venture funding. In August the company was named an advanced tier technology partner in the Amazon Web Services Partner Network.
CEO: Derek Smith
Businesses are heavily investing in big data initiatives for operational and analytical purposes. But those projects may be doomed to failure if they are working with poor-quality data.
Naveego's cloud-based software provides data quality and master data management tools that help organizations monitor and manage the quality of their business data – whether on-premises or in the cloud – and leverage it for competitive advantage.
Naveego, founded in 2013 and based in Traverse City, Mich., launched its first channel program in October and is recruiting data management consultants, systems integrators and managed service providers.
CEO: Saket Saurabh
Nexla has developed a data operations platform that uses machine-learning technology to monitor, adapt and securely move data between companies in real time. By automating such data operations, the Nexla argument goes, companies can more quickly derive value from their data with minimal engineering.
Founded just last year, Millbrae, Calif.-based Nexla released a public beta of its product in May. At the same time the company raised $3.5 million in seed financing.
Nexla caught everyone's attention when it won the top prize in the Startup Showcase at the Strata + Hadoop World conference in March.
CEO: Harry Glaser
Periscope Data's core product, Periscope Data Analytics, provides users with a way to run SQL queries against data residing in multiple database systems, generating interactive dashboards and charts that can be shared throughout a company.
In November the company launched the Unified Data Platform, which the company says addresses the complete analytics life cycle, allowing data teams to ingest, store, analyze, visualize and report on data.
Founded in 2012 by managers from Google and Microsoft, Periscope Data is based in San Francisco. In August the company said its annual recurring revenue had increased by 322 percent since 2016.