There is an emerging field of companies looking to take on the challenges presented by the roiling tide of big data. While their visions vary, each has identified a market need that it believes its technology uniquely addresses. Here, DBTA highlights the approaches of 10 companies we think are worth watching.
With a mission to bring big data to the desktop, Cirro offers a product suite designed to simplify data access and exploration across heterogeneous data sources. Cirro solutions are cloud-based and can run on public, virtual private and on-premise cloud environments and integrate with existing data warehouse and analytic investments.
2. Citus Data
Earlier this year, Citus Data released CitusDB 2.0, its analytics database built on top of PostgreSQL. Key features of the company’s technology include a query engine that distributes SQL queries and runs them in parallel across commodity hardware, as well as the ability to run SQL queries on Hadoop clusters without having to load any data into the database.
3. ClearStory Data
ClearStory Data’s solution is designed to help business users conduct self-driven big data exploration—making it easier to gather and explore big, diverse, dispersed data from corporate data sources, Hadoop, and the web. “In 2011, the global output of data increased 62%, yet there’s a massive shortage in the number of qualified data professionals to process this data,” says Sharmila Shahani-Mulligan, CEO and a founder of ClearStory Data.
4. Concurrent, Inc.
Founded in 2008 by Chris K. Wensel, the author of the open source Cascading project, Concurrent seeks to simplify big data application development, deployment, and management on Apache Hadoop. The company has launched Cascading, a technology for building big data applications, as well as Lingual, an open source project that delivers ANSI-standard SQL technology to build new and integrate existing applications onto Hadoop.
5. Digital Reasoning Systems, Inc.
Digital Reasoning develops and markets solutions that provide automated understanding for big data. Following the events of 9/11, the company, which was founded by Tim Estes and Dorothy Currey, initially set out to provide analytics for unstructured data for the US intelligence community. The company’s flagship product Synthesys can read, resolve, and reason across hundreds of millions of documents to automatically understand and isolate critical information such as risks, opportunities, and anomalies.
Launched in 2009 by Nick Lavezzo, Dave Rosenthal, and Dave Scherer and headquartered in Vienna, Virginia, FoundationDB’s stated mission is to provide data storage technology that frees engineers and companies to focus on problems other than building their data stack. To address that need, FoundationDB provides database technology that combines the advantages of NoSQL databases with the reliability of ACID transactions.
7. JethroData, Inc.
Founded by Eli Singer, Boaz Raufman, and Ronen Ovadya, with offices in Israel and New York, JethroData seeks to provide analytic database technology that runs natively on Hadoop and lets nontechnical users interactively explore data and quickly get answers, using standard SQL or common BI tools.
8. ParStream GmbH
Real-time big data analytics provider ParStream was founded in 2008 by Michael Hummel and Jörg Bienert, after they identified a gap in the way existing database technologies handled big data analyses. They were joined by a third co-founder, Norbert Heusser, an expert in performance analytics and tuning. ParStream provides a distributed, massively parallel processing columnar database based on a shared nothing architecture. High peformance compression is a key aspect of the technology, enabling the delivery of both big data and fast data.
9. Splice Machine, Inc.
Splice Machine is the developer of a SQL-compliant database designed for big data applications. Built on the Hadoop stack, the Splice SQL Engine enables application developers to build web, mobile, and social applications that scale while leveraging SQL tools and skill sets. In talking with prospective customers about their requirements, the ability to leverage SQL skills has emerged as the number-one point, according to chairman and CEO Monte Zweben.
With the aim of making big data accessible to all businesses, Xplenty has developed a code-free Hadoop as a service big data platform specifically geared toward data warehousing specialists, BI developers, and ETL developers. Xplenty lets users manipulate their data in a code-free and scalable cloud-based environment, thereby eliminating the need for both a programmer and the need to purchase hardware to host business software.