BlueTalon Extends Data-Centric Security Platform to Support Apache Spark

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BlueTalon-logoBlueTalon®, the leader in Data-Centric Security, announced the immediate availability of its Data-Centric Security solution for Apache® Spark™, making it the first company to provide a unified data security layer across Hadoop, Hive, Spark and the multiple data platforms commonly used for big data. Using BlueTalon, organizations eliminate security blind spots and gain unprecedented visibility and control directly at the data layer.

Data security, privacy, and compliance is top-of-mind for data-driven businesses,” said Eric Tilenius, CEO at BlueTalon. “Companies should tackle data breaches with data-centric security rather than expensive and now ineffective perimeter defenses. As the first vendor to bring data-centric security to Apache Spark, we enable enterprises to unlock the full potential of new data initiatives without compromising compliance and security.”

Enterprises are augmenting their data infrastructure using Spark as a fast access layer for their big data projects, next to Hive and Pig as data ingestion and transformation tools. They can now rely on BlueTalon to eliminate security one-offs and maintain consistent data protection across all components deployed.

The promise of big data is to scale and democratize access to data,” says Yann-Landrin Schweitzer, Senior Architect at Autodesk. “Modern query engines like Apache Spark put this within reach, with interactive querying, practical SQL access, BI tools, and agile development. Unfortunately, regulatory and contractual requirements always add constraints to data access. The holy grail for big data is to go beyond better access to data to also provide more secure access, so that the full value of big data can be realized without incurring significant legal risks.”

From relational databases to Hadoop – Hive, Impala, and HDFS – and now Spark, BlueTalon enforces consistent, precise, and dynamic security controls with:

  • Precise data authorization: define access control down to the finest data element for each platform;
  • Flexible, contextual, and business-oriented policies based on roles and attributes to help bridge the gap between business stakeholders and security engineers;
  • Dynamic data masking and stealth analytics to protect sensitive data from unauthorized users;
  • Audit trail of data consumer built at the level of granularity required by regulations and industry standards.


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