What they do: Develop software that transforms raw data in Hadoop into interactive, in-memory business intelligence
Headquarters: San Mateo, CA
CEO: Ben Werther, who was previously VP of Products at DataStax.
Funding: $27.2 million to date from Andreessen Horowitz, Battery Ventures, Sutter Hill Ventures and In-Q-Tel.
Why they're on this list: They're focused on the main challenge of Big Data, namely, how to make sense of it. They have a solid management team and an impressive amount of VC funding.
While businesses have been rapidly adopting Apache Hadoop as a scalable and inexpensive solution to store near-infinite amounts of data, they struggle to extract value from that data. Traditional relational database and analytics tools just can't deal with massive amounts of structured and unstructured data. So businesses must perform a complex and rigid set of steps between the customer interactions that generate data and analyzing that data with business intelligence (BI) software. These steps include ETL (extract, transform, load) processing, building a data warehouse and connecting to a visualizer tool. Business users are required to be experts who understand MapReduce or SQL coding in order to access the data.
Platfora tries to simplify that process and automatically transform raw data in Hadoop into interactive, in-memory business intelligence, with no ETL or data warehousing required. Platfora provides an exploratory BI and analytics platform designed for business analysts and not just IT.
Edmunds.com is an early customer.
Competitors: SAS, Alpine Data, Platfora, Skytree, Revolution Analytics and Rapid-I.
What they do: Provide a Hadoop-based, SQL-compliant database designed for Big Data applications
Headquarters: San Francisco, CA
CEO: Monte Zweben. Zweben’s early career was spent with the NASA Ames Research Center as the Deputy Branch Chief of the Artificial Intelligence Branch. Later, he founded and served as CEO of Red Pepper Software and then Blue Martini Software.
Founded: October 2012
Funding: They are backed by $4 million in funding from Mohr Davidow Ventures.
Why they're on this list: As Hadoop and NoSQL platforms catch on, users eventually run into a problem: limited SQL support is forcing users to rewrite existing apps or BI reports, which a very costly process. Splice Machine argues that Big Data and application developer communities need a more cost-effective database to power their applications—one that combines the scalability and availability of NoSQL with the power and popularity of SQL.
Built on the Hadoop stack, the Splice SQL Engine enables application developers to build hyper-personalized web, mobile and social applications that can achieve Big Data scale, but the platform also allows users to leverage the ubiquity of SQL tools and skill sets in the marketplace.
Splice Machine contends that other "SQL on Hadoop" products (such as Apache Hive) are read-only, analytics-only solutions. Those analytics solutions cannot support real-time updates and ACID (Atomicity, Consistency, Isolation, Durability) transactions. Splice Machine is designed to support both operational (OLTP) and analytic (OLAP) workloads with real-time queries.
Competitors: Apache Hive, Cloudera Impala, Apache Drill
Jeff Vance is a Santa Monica-based writer. He's the founder of Startup50, a site devoted to emerging tech startups, and he also founded the content marketing firm, Sandstorm Media. Connect with him on Twitter @JWVance.