The 10 Coolest Big Data Startups Of 2015 (So Far)
Super-Fast Growth, Super-Cool Startups
Big data remains one of the fastest-growing segments of the IT industry with researcher Wikibon predicting that the big data technology market will grow nearly 22 percent to $33.31 billion this year.
In the last year, it seems the focus among startups in the big data arena has been on helping businesses more easily and effectively analyze data and derive value from it. They include companies offering technology for analyzing data in Hadoop and realtime streaming data, and companies providing software that brings big data analytics capabilities to everyday business workers.
Here are 10 of the coolest big data startups of the year (so far).
CEO: Ed Miller
San Francisco-based DataHero is focused on developing "self-service" business analytics software. The DataHero cloud-based service collects data from such disparate sources as Box, Dropbox, Google Drive, Excel, Office 365, Marketo, HubSpot and Eventbrite, and turns it into charts and dashboards.
For the business analytics software industry, the challenge has been developing analytical applications that can be used by a broad range of everyday business users without a lot of assistance from the IT department. DataHero is among the few companies that's close to achieving that.
DataHero, founded in 2011, raised $6.1 million in Series A funding in May.
CEO: Andy Palmer
You have to love a company whose stated goal is battling the evils of "schema proliferation." Tamr, based in Cambridge, Mass., develops enterprise data unification software that businesses use to integrate diverse, siloed data for business analytics tasks and downstream applications.
Tamr is the latest brainchild of database luminary Michael Stonebraker, who started the company in 2013 with fellow database industry veteran Andy Palmer. (Palmer serves as CEO while Stonebraker is CTO.) The two previously started Vertica Systems, now owned by Hewlett-Packard.
CEO: Josh James
Domo was in stealth mode between its 2010 launch and earlier this year, but interest in the cloud-based executive management system the company had under development was already high. In April, the American Fork, Utah-based company debuted its application that provides business managers with access to information scattered across many disparate sources through a single dashboard.
But what really got people's attention was the news the company had raised an eye-popping $200 million in Series D funding, putting the company's total financing at around $450 million and its valuation at approximately $2 billion.
CEO: Sushil Thomas
An increasing number of businesses are implementing Hadoop systems, using them to collect huge volumes of disparate data from multiple sources. But making use of that data isn't so easy -- most traditional business analytics tools can't directly access Hadoop data, and IT departments have to step in to prepare the data or move it to another system to make it available for everyday business workers.
Arcadia Data is developing visual analytics software that overcomes those hurdles by directly accessing data stored in Hadoop clusters. The technology uses Hadoop as an operating system, allowing it to run directly on Hadoop servers and access data stored in the Hadoop Distributed File System.
San Mateo, Calif.-based Arcadia launched Arcadia Instant, a free download of the data visualization tool, in June with plans to finish and ship the complete platform by the end of this year.
CEO: Frank Bien
Looker provides a Software-as-a-Service business analytics platform that the company said puts actionable intelligence in the hands of the employees who need it most. The cloud-based tools can connect to a wide range of data sources, including Amazon Redshift, Google BigQuery, HP Vertica, Cloudera Impala, Apache Spark, SQL databases and others.
In May, the Santa Cruz, Calif.-based company began offering a "Powered by Looker" service that allows businesses and cloud software developers to embed the Looker analytical functionality within any application, website or portal. The idea is that businesses and partners can quickly deploy data analytics tools to their own customers.
CEO: Praveen Kankariya
Kyvos Insights is another startup that seeks a better way to analyze data stored in Hadoop clusters. Specifically, the Los Gatos, Calif.-based company developed OLAP (online analytical processing) software that carries out interactive, multidimensional analysis tasks on huge volumes of structured and unstructured Hadoop data.
Kyvos Insights just came out of stealth mode in June, and its software is running in several early-customer Hadoop environments in the financial service industry.
CEO: Jay Kreps
One of the biggest challenges in big data is working with high volumes of realtime streaming data. One technology that's catching on for tackling the problem of streaming data is Apache Kafka, an open-source, highly scalable messaging system that can be used in conjunction with other technologies to provide realtime analysis and rendering of streaming big data.
Confluent was launched in September 2014 to provide technology and services that help businesses adopt and use the Kafka system. Based in Mountain View, Calif., Confluent was co-founded by Jay Kreps, Neha Narkhede and Jun Rao, who created Kafka while working at LinkedIn. Earlier this month, Confluent raised $24 million in Series B funding.
As more businesses implement Internet-of-Things systems to collect and analyze huge volumes of streaming data, Kafka could prove to be a critical technology. And Confluent could play a major role in its adoption.
CEO: Dave Mariani
While more corporate data is being collected and stored in Hadoop, there are few straightforward ways to access and analyze that data with the reporting and business analytics tools many information workers use today. And that's proving to be a stumbling block for many big data projects.
AtScale, founded in 2013, aims to bridge that disconnect. The San Mateo, Calif.-based company exited stealth mode in April and debuted its AtScale Intelligence Platform software that allows commonly used business intelligence tools to access data stored in Hadoop clusters. The technology creates a semantic layer between Hadoop and business analytics tools, turning Hadoop into an OLAP server.
CEO: Ajeet Singh
Under the mantra "search-based analytics for everyone," ThoughtSpot wants to eliminate the need for complex BI tools. The company's ThoughtSpot Relational Search Appliance combines data from on-premise, cloud and desktop sources, and provides users with the ability to access that data with a simple search interface.
ThoughtSpot, founded in 2012 and based in Palo Alto, Calif., launched its appliance product in October 2014. Four months earlier, the startup raised $30 million in Series B financing.
CEO: Ann Johnson
Interana is another big data startup that's developing technology to help businesses analyze streaming data in realtime.
The company's events-based analytical software works with clickstream data and other "events-based" information to help users answer questions about how customers behave and how products are used. The goal is to provide actionable business intelligence for nontechnical users.
Interana was founded in 2013 and just exited stealth mode last fall. The Menlo Park, Calif.-based company raised $20 million in Series B financing in January.