If Data Is The New Oil, NoSQL Is The Supertanker.
Developers building next-generation applications for web, mobile, cloud, or IoT have a limitless set of choices for how and where they want to store data. NoSQL databases are a relatively new, more scalable way to store data, and can manage large amounts of structured, semi-structured, and unstructured data. They allow organizations to be more flexible and scalable with massive data growth – storing sensitive and personal data, network data, and any type of business data.
On the flip side, it can be difficult to manage data in NoSQL: it’s more complex, there’s no standard way to retrieve information, and traditional classification, privacy, and security technologies are rarely built with NoSQL in mind.
NoSQL has “become critical for all business to support modern business applications” – because of this, it’s more critical than ever to be able to classify and manage that data.
Discovery Drama for NoSQL
One of the biggest challenges to meet any type of data privacy regulation is to be able to discover, identify, and classify data across multiple data stores. Data privacy regulations require organizations to identify and manage consumer data regardless of where it’s stored.
Classification software is traditionally built for on-premises, unstructured, or structured SQL data. With the explosion of data, however, more organizations are moving their personal and sensitive information to the cloud or to Big Data & NoSQL stores like MongoDB, Elastic, CouchBase, Cassandra, and more.
Some of the challenges to discovering and classifying data in NoSQL include:
• Flexible Schemas: One of the strengths of NoSQL is that they don’t have a fixed schema: that makes it more flexible, scalable, and able to adapt to different types of data use. That same strength, however, turns out to be a challenge in the context of data discovery: every record could have different fields, and it’s difficult to represent the findings in a consistent way.
• Unique to a fault: Unlike SQL, there’s no standard way to retrieve information for NoSQL: each system requires specific handling. While structured data sources typically comply with ANSI SQL, every NoSQL data source is unique.
• Performance anxiety: Since NoSQL often contains big data, anything that’s accessing that data needs to be mindful of structure and indexing – and purpose-built for this specific type of data storage – so it doesn’t slow down performance.
• Late to the party: Because NoSQL is still relatively new, traditional classification, privacy, and security technologies are rarely built with NoSQL in mind.
Since many legacy classification technologies aren’t built to scale to the cloud, NoSQL, or BigData, it’s challenging for companies that want to find, inventory and catalog their personal data everywhere for regulations like CCPA y GDPR.
Being able to aggregate and classify data from disparate sources is an essential component in the new era of data privacy and data protection regulations – especially now that developers regularly keep sensitive data in all kinds of non-traditional, non SQL data stores.
A BigIDea for NoSQL
BigID is the first data discovery technology that empowers security and data professionals with the ability to find your sensitive and personal data anywhere: structured, unstructured, big data, cloud, and NoSQL.
BigID can even correlate identity data across systems: linking a record in an SQL database with documents stored in a NoSQL environment to the same identity or entity.
With BigID, organizations can go beyond discovery to build identity profiles and a personal data inventory that spans across their files, relational databases, data warehouses, NoSQL, and more – creating a 360° view of personal and sensitive data.
And it doesn’t stop there: with BigID, organizations can fulfill solicitudes de acceso de interesados (DSAR) across NoSQL as well.
BigID provides organizations unmatched NoSQL support – from MongoDB to CouchBase to Cassandra, AWS Dynamo, Elastic and more. Organizations can then see that data in context with information stored across the cloud, traditional data stores, and applications to build comprehensive identity and entity profiles, enabling compliance and data protection for consumer data.
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