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Tonic.ai And MongoDB Roll Out Data Protection Integration

Tonic.ai And MongoDB Roll Out Data Protection Integration

 Customers Using MongoDB Can Now Mimic Document-based Data

Tonic.ai, the synthetic data company pioneering data de-identification, subsetting, and synthesis to get developers the data they need, without breaching privacy, has announced an integration with MongoDB, a leading document-oriented NoSQL database used for high volume data storage. MongoDB customers can now use Tonic’s data mimicking solution to de-identify and protect private information captured in customer profiles, webforms, financial transactions, medical records, and much more.

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Tonic’s all-in-one data mimicking platform provides privacy guarantees while rapidly equipping developers with the data they need to do their best work. By seamlessly integrating data de-identification, subsetting, and synthesis into modern CI/CD pipelines, Tonic is helping its customers shorten development cycles by as much as 60%, eliminate cumbersome data pipeline overhead, and mathematically guarantee the privacy of their data.

The integration with MongoDB is the latest addition to the growing list of databases that Tonic natively connects to, including Amazon Redshift, Databricks, BigQuery, Spark on Amazon EMR, and Db2. What makes it particularly noteworthy is its NoSQL, document-based nature. The nested data structures of NoSQL databases can be unpredictably complex. They often lack structure, and data types within the same element may vary across documents. To overcome these challenges, Tonic builds a unique hybrid document model that parallels a relational schema, to fully capture the nested data structure’s complexity and safely carry it over into lower environments.

By enabling customers to work with data across database types, Tonic allows companies to mimic their entire data ecosystems, from traditional relational databases to data warehouses to NoSQL document-based databases.

“Tonic’s database-agnostic nature allows companies to connect directly to a database, as opposed to a data-upload approach. These are two of our key differentiators as compared to other data anonymization and synthesis tools on the market,” said Ian Coe, CEO of Tonic.ai. “When you add the rare ability to work with document-based data in MongoDB, we’re excited to be leading the charge in getting developers and data engineers the safe, realistic data they need.”

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