To dramatically increase the ROI that corporations can gain from their big data, Xcalar announced availability of its business analytics platform, Xcalar 1.2, which gives the fastest, easiest, and most cost-effective access to actionable insights from big data.
Xcalar also announced it has secured over $21 million in venture funding to date with its Series A round led by Khosla Ventures. Other investors include industry visionaries Andy Bechtolsheim and Diane Greene, and Silicon Valley venture capital firm, Merus Capital.
Co-founded by former Oracle technologist Vikram Joshi, and Rebecca Ye, an early founder of Google Cloud Platform and previously an Oracle sales exec, Xcalar has been quickly catching the attention of the technology elite and top-tier customers:
- Xcalar inked partnerships with Microsoft, Google, Tableau, Confluent, and MapR, and is currently working on deployments and pre-production pilots with about a dozen Fortune 100 companies as well as the government
- Microsoft selected Xcalar as one of the top startups from over 1,000 in its coveted Accelerator Program
- CIO Review rated Xcalar as one of Google’s top-20 technology partners
At Xcalar we set out to create a visual design platform that leverages existing investments in Hadoop, eliminates the need for most big data programming languages, and allows business analysts, data engineers, and data scientists to work relationally with modern data in interactive time. Today we have achieved these goals,” says CEO Vikram Joshi. “With Xcalar 1.2, businesses, large organizations, and governments can extract critical insights from all their data sources, including images and media. They can use our visual programming to benefit from powerful open source technologies such as Google TensorFlow.” Vikram previously founded ioTurbine and PixBlitz Studios, and is an engineering veteran of Oracle, SGI, and Sun Microsystems.
Key benefits of Xcalar 1.2 include:
- User-friendly UI/UX that does not require programing skills to design models, create queries, synthesize schemas, build regression analysis algorithms, and even design new Machine Learning algorithms
- Scale-out to hundreds of nodes, thousands of users, and petabytes of data
- Point-and-click access to directly read all data types (semi-structured, unstructured, and structured) stored in the cloud or on-prem (Amazon S3, Microsoft Azure Storage, Google Cloud Storage, HDFS, SAN, NAS, NFS, or local file systems)
- On-prem or in the cloud deployment
- Seamless integration with leading visualization tools such as Tableau, Microsoft Power BI, Looker, Domo, Qlik, and a variety of reporting tools
- Ability to work with thousands of filter, aggregate, sort, map, join, group-by, merge, union, correlation, and complex relational, statistical and ML operations, in series or parallel, to solve deep analytics problems
- Detailed dataflow graphs to track data lineage of any given field from its source so audit requirements and regulatory compliance are easily met
Xcalar represents a fundamental shift in the big data landscape,” said Vinod Khosla. “Xcalar closes the gap between big data and the business analysts to help ask the right questions and find meaningful insights in meeting real business challenges. No existing technology comes close to delivering on that promise. It’s hard to compare all the competing claims in the big data space. Xcalar got it right by rethinking the whole end-to-end process — from raw data to modeling, design, and query formulation, to execution — accelerating the most critical benchmark for businesses: ‘time-to-insight.'”
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