SANTA CLARA, Calif., June 01, 2022 (GLOBE NEWSWIRE) – Baffle, Inc.. today announced the existence of Baffle Data Protection Service (DPS) Transform which goes with Apache Kafka® and Confluent Cloud. Developers, data engineers, and operators can now benefit from automated data de-identification and protection as information is captured in the cloud and used by applications.
Baffle DPS Transform got verification from Confluent as part of Confluent Verified Integrations Program. Verification ensures that connectors meet the technical and functional requirements of the changes for Kafka using the consumer/producer API. It provides customers with a level of compatibility and functionality in the Confluent Cloud or Confluent Platform ecosystem and it is a supported integration between the Confluent Cloud or Confluent Platform and Baffle Data Protection Services. Baffle DPS Transform can be found at https://www.confluent.io/hub/baffleinc/baffle-transforms.
Moving enterprise data to the cloud is not a one -time increase and transfer. Data permeates every aspect of the business and is now virtually constantly flowing from millions of locations and devices. As streaming and scale intensifies, organizations typically encounter performance bottlenecks, forcing significant re-engineering of business applications and processes to secure the data pipeline.
Baffle automatically transforms data as it quickly enters the pipeline using a plug-in that uses Single Message Transform (SMT) capability, does not recognize sensitive data immediately, and controls who can access and use data that’s business. By integrating Baffle’s code-free, simple-to-deploy security mesh solution with Apache Kafka, users can now securely move large data workloads to the cloud quickly and securely without performance impact and without modification in the application.
Kafka is a distributed event streaming platform capable of handling trillions of events in a day. Baffle, Kafka, and Confluent customers will now have the simplified integration of security controls into an Apache Kafka stream with Baffle DPS Transform. Customers can use Baffle for a variety of real-time use cases, including fast and secure information transfer to the cloud without having to ingest, transform, and clean large data. team. This data -centric security approach ensures that no explicit text data is exposed in the analytics pipeline, preventing the possibility of sensitive data being stolen.
“The race to securely move massive amounts of data across cloud pipelines is fraught with stumbling blocks 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 speeds up secure cloud data migration five times faster by easily embedding the current data pipeline and automatically identifying data as it is digested and used across the enterprise.”
Join Baffle here webinar on how companies can apply modern data protection techniques and technologies to easily identify and redefine Kafka data streams to securely share sensitive information between internal and external audiences and domains of data.
About Baffle
Baffle protects data in the cloud through “no code” and “low code” data security mesh. The solution provides universal data protection to secure data wherever it resides and as it is used in distributed data environments. Companies can control who can see what data has this layer of security without impacting performance on the user experience. Proven in large-scale environments, the Baffle Data Protection Service only de-identifies sensitive information with its rapid processing in the cloud. Without application changes, security teams can move sequentially with business initiatives to move 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 at LinkedIn.
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