EQNX::TICKER_START (NYSE:NOW), EQNX::TICKER_END Baffle, Inc. today announced the availability of the Baffle Data Protection Service (DPS) Transform that integrates with Apache Kafka(R) and Confluent Cloud. Developers, data engineers, and operators can now benefit from automated data de-identification and protection as information is ingested into the cloud and used by applications.
The Baffle DPS Transform has earned verification from Confluent as part of the Confluent Verified Integrations Program. The verification ensures that connectors meet the technical and functional requirements of transforms for Kafka that use the consumer/producer API. This provides customers a level of compatibility and functionality with the Confluent Cloud or Confluent Platform ecosystem and is a mutually supported integration between Confluent Cloud or Confluent Platform and Baffle Data Protection Services. The Baffle DPS Transform can be found at https://www.confluent.io/hub/baffleinc/baffle-transforms.
Migration of enterprise data to the cloud is not a one-time lift and shift. Data permeates every aspect of business and now streams almost constantly from millions of locations and devices. As streaming and scale intensify, organizations typically hit performance bottlenecks, forcing significant re-engineering of applications and business processes to secure the data pipeline.
Baffle automatically transforms data on the fly as it moves into the pipeline with a plug-in that utilizes the Single Message Transform (SMT) capability, de-identifies sensitive data on the fly, and controls who can access and use that data in the business. With the integration of Baffle's no-code, simple-to-deploy security mesh solution with Apache Kafka, users can now securely move large data workloads to the cloud quickly and securely with no performance impact and no application changes.
Kafka is a distributed event streaming platform capable of handling trillions of events a day. Baffle, Kafka, and Confluent customers will now have simplified integration of security controls into an Apache Kafka stream with the Baffle DPS Transform. Customers can use Baffle for various real-time use cases, including moving information quickly and securely in the cloud without big teams having to ingest, transform, and cleanse data. This data-centric security approach ensures that no cleartext data is exposed in the analytics pipeline, preventing the possibility of sensitive data from being stolen.
"The race to safely migrate massive amounts of data into cloud pipelines is filled with stumbles and stalls, often requiring significant application re-engineering and business process changes that increase risk and slow down time-to-value," said Ameesh Diavatia, co-founder and CEO, Baffle. "Baffle accelerates secure cloud data migration speed five-fold by easily embedding in the existing data pipeline and automatically de-identifying data as it is ingested and used across the enterprise."
Join Baffle in this webinar on how companies can apply modern data protection approaches and technologies to easily de-identify and re-identify Kafka data streams to share sensitive information securely between internal and external audiences and data domains.
Baffle protects data in the cloud via a "no code" and "low code" data security mesh. The solution provides universal data protection to secure data wherever it lives and as it is consumed in distributed data environments. Companies can control who can see what data with this security layer with no performance impact on the user experience. Proven in large-scale environments, only the Baffle Data Protection Service de-identifies sensitive information on the fly as it is processed in the cloud. With no application changes, security teams can move in lockstep with business initiatives to move more data and workload to the cloud faster. Investors include Celesta Venture Capital, National Grid Partners, Lytical Ventures, Nepenthe Capital, True Ventures, Greenspring Associates, Clearvision Ventures, Engineering Capital, Triphammer Venture, ServiceNow Ventures [NYSE: NOW], Thomvest Ventures, and Industry Ventures. Follow us on Twitter and LinkedIn.
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