Diskover vs Varonis Data Discovery and Classification

Diskover indexes files across storage platforms and brings their metadata into a searchable catalog for unstructured data management. It is designed for large estates, including those with billions of files. A distributed engine scans in parallel and can reuse cached results to speed later indexing. Diskover indexes metadata without moving or copying underlying data and offers browser-based access. The catalog combines core file details with enriched business and technical attributes. Rules and plugins automate cleanup, tagging, tiering, and repetitive tasks; the maker describes more than 50 plugins for enrichment, workflow automation, data movement, and file actions that need no code. Listed integrations include Azure Blob, OneDrive and SharePoint, Amazon S3 and compatible storage, Grafana, Dell PowerScale, and Snowflake. Multistream includes a connector to data lakes and lakehouses and curated datasets for AI/BI pipelines. An optional AI connector supports natural-language interaction on desktop or mobile and use of a customer's chosen LLM. Plans have annual platform fees, but dollar prices are not published; pricing is available on request.

Varonis Data Discovery and Classification helps organizations locate and classify sensitive information across cloud, SaaS, data center, hybrid, and on-premises environments. It scans structured databases and warehouses, unstructured files and folders, and semi-structured SaaS apps and email. Out-of-the-box policies, rules, and models are intended to find sensitive data without configuration or training data. Varonis says its pattern matching and AI classify PII, PCI, PHI, passwords, secrets, and tokens with 98% accuracy. The product creates a file-level inventory that can be prioritized by exposure, activity, density, metadata, size, and staleness. It can find exposed or stale sensitive data, monitor suspicious activity, and alert on it. It can apply missing labels, correct incorrect labels, and enhance Microsoft native classifications through MPIP integration. Incremental scans check created or changed files. Varonis says its AI models can run on local compute so data need not leave the environment for scanning. Listed integrations include Microsoft 365, AWS, Azure, Google Cloud, Salesforce, Box, Databricks, and ServiceNow. Pricing is by quote.