Tonic.ai Announces Collaboration with MongoDB
Customers of MongoDB can now use Tonic’s data mimicking solution to de-identify and secure personal data stored in customer profiles, webforms, financial transactions, medical records, and other places.
FREMONT, CA: Tonic.ai, the synthetic data business that pioneered data de-identification, subsetting, and synthesis to bring developers the data they need without violating the privacy, has announced a partnership with MongoDB, a premier document-oriented NoSQL database for high-volume data storage. Customers of MongoDB can now use Tonic’s data mimicking solution to de-identify and secure personal data stored in customer profiles, webforms, financial transactions, medical records, and other places.
“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 today,” said Ian Coe, CEO, Tonic.ai. “When you add the rare ability to work with document-based data in MongoDB, were excited to be leading the charge in getting developers and data engineers the safe, realistic data they need.”
Tonic’s all-in-one data mimicking platform ensures developer privacy while providing them with the data they need to do their best work quickly. Tonic is helping its customers speed development cycles by as much as 60 percent, eliminate burdensome data pipeline overhead, and mathematically ensure the privacy of their data by seamlessly integrating data de-identification, subsetting, and synthesis into modern CI/CD pipelines.
MongoDB is the newest database to join Tonic’s growing collection of native connections, including Amazon Redshift, Databricks, BigQuery, Spark on Amazon EMR, and Db2. The fact that it is document-based and uses NoSQL makes it stand apart. NoSQL databases’ nested data structures can be unpredictably complicated. They are frequently unstructured, and data types within a single element may differ throughout texts. To solve these obstacles, Tonic creates a hybrid document model that is similar to a relational schema, allowing it to properly capture the complexity of nested data structures and safely transport it over to lower contexts.
Tonic allows enterprises to replicate their complete data ecosystems, from traditional relational databases to data warehouses to NoSQL document-based databases, enabling customers to engage with data across database types.