BEDROCK DATA VS VARONIS
Stop carrying the scanning tax
Your data estate should not become more expensive to understand as it grows. Compare Varonis with an in-place, serverless architecture that scales up for the work and back to zero when it is done.
The short version
Full coverage, no capacity plan.
Bedrock Data expands ephemeral compute for the work instead of requiring a permanent scanning fleet sized around peak demand.
Petabytes in hours.
Adaptive Scanning reduces redundant processing so large data estates can be analyzed continuously without brute-forcing every object.
Measure exposure, not scan volume.
Connect classification to effective access, identity, and activity so the team can see which sensitive data is actually at risk.
One context layer for AI.
Use the same data and identity context to understand what supported agents can reach and govern what happens when they use it.
Scale back to zero.
Discovery and classification run inside your environment. When the work is complete, Bedrock Data leaves no permanent scanning fleet running.
How Bedrock Data compares
Varonis | Bedrock Data | |
|---|---|---|
Scaling model | Varonis describes parallelized scanning nodes in the customer private cloud, with resources added as the estate grows. | Serverless Outposts expand and rebalance automatically for each scan, then scale back to zero when the work is complete. |
Scanning model | Classification runs on parallel scanning nodes near the data. After the initial scan, activity monitoring identifies newly created or changed data for incremental scanning. | Masterless, ephemeral compute scales horizontally for discovery and classification without leaving long-running scanner infrastructure behind. |
Coverage economics | Growing the estate can require additional customer-cloud scanning resources. Validate the initial scan cost, refresh cost, and infrastructure footprint at your volume. | Adaptive Scanning groups structurally similar data and intelligently selects representative samples, reducing redundant processing at petabyte scale. |
Data and access | Mature permissions analysis, activity monitoring, and automated remediation across supported environments. | One graph connecting sensitivity, entitlements, effective access, identity, activity, and business context. |
AI security | Atlas takes a broad AI platform approach across inventory, posture, testing, governance, and inline gateway controls. | Bedrock Data focuses on the data risk AI creates: what supported agents can reach, what they do with it, and how policy is enforced through supported gateways. |
Data handling | Varonis states that its local collector keeps sensitive data in the customer environment and sends metadata to its cloud. | Zero Data Access keeps discovery and analysis inside the customer environment and sends documented metadata to the Metadata Lake. |
Context and integrations | Data context primarily powers monitoring, analysis, and remediation within the Varonis platform. | The Metadata Lake distributes context into security, governance, access, AI, and ticketing workflows through APIs and integrations. |
Scaling model
Varonis
Varonis describes parallelized scanning nodes in the customer private cloud, with resources added as the estate grows.
Bedrock Data
Serverless Outposts expand and rebalance automatically for each scan, then scale back to zero when the work is complete.
Scanning model
Varonis
Classification runs on parallel scanning nodes near the data. After the initial scan, activity monitoring identifies newly created or changed data for incremental scanning.
Bedrock Data
Masterless, ephemeral compute scales horizontally for discovery and classification without leaving long-running scanner infrastructure behind.
Coverage economics
Varonis
Growing the estate can require additional customer-cloud scanning resources. Validate the initial scan cost, refresh cost, and infrastructure footprint at your volume.
Bedrock Data
Adaptive Scanning groups structurally similar data and intelligently selects representative samples, reducing redundant processing at petabyte scale.
Data and access
Varonis
Mature permissions analysis, activity monitoring, and automated remediation across supported environments.
Bedrock Data
One graph connecting sensitivity, entitlements, effective access, identity, activity, and business context.
AI security
Varonis
Atlas takes a broad AI platform approach across inventory, posture, testing, governance, and inline gateway controls.
Bedrock Data
Bedrock Data focuses on the data risk AI creates: what supported agents can reach, what they do with it, and how policy is enforced through supported gateways.
Data handling
Varonis
Varonis states that its local collector keeps sensitive data in the customer environment and sends metadata to its cloud.
Bedrock Data
Zero Data Access keeps discovery and analysis inside the customer environment and sends documented metadata to the Metadata Lake.
Context and integrations
Varonis
Data context primarily powers monitoring, analysis, and remediation within the Varonis platform.
Bedrock Data
The Metadata Lake distributes context into security, governance, access, AI, and ticketing workflows through APIs and integrations.
Comparison reflects public vendor materials and Bedrock Data product documentation as of September 2026. Validate product scope, performance, and commercial terms in your own environment.
Where the old operating model breaks
Coverage becomes a budget decision
When understanding more data requires proportionally more infrastructure, teams are pushed to narrow scope, lengthen scan intervals, or accept higher customer-cloud spend.
Capacity planning becomes security work
Scanner sizing, placement, tuning, and maintenance consume time that should be spent reducing risk. SaaS delivery does not automatically remove customer-side infrastructure.
Classification volume hides the real measure
The goal is not to produce the largest list of sensitive files. It is to identify which sensitive data is exposed, who can reach it, and what should be fixed first.
AI multiplies consumption faster than scans
Agents can read across stores and tools at machine speed. Security needs persistent context about what they can reach, not another disconnected inventory.
Built differently.
Proven where others break.
Full coverage. No cost tradeoffs.
Adaptive Scanning and serverless scale-out are designed to cover very large data estates without brute-forcing every object.
Real exposure. See effective access.
Resolve nested groups, federated identities, roles, service accounts, and supported AI systems, then connect that reach to sensitive data.
Zero Data Access. Your data stays put.
Raw customer data remains inside your boundary while Bedrock Data builds the metadata context needed for security and governance.
Metadata lake. Context works everywhere.
Put shared data context behind incident response, access reviews, governance, AI controls, and the tools already in your stack.
One estate. One measurable operating model.
Bedrock’s Metadata Lake connects sensitivity, entitlements, activity, ownership, and AI access while the scanning layer expands only when work needs to be done. Test the difference on your largest or most expensive datastore. Compare coverage, time to useful findings, cloud infrastructure, false positives, and ongoing administration.
