Sentra vs Concentric

Compare Sentra versus Concentric across features, performance, and customer satisfaction to make the right choice for your organization.

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Sentra Named a Leader and Fast Mover in 2025 GigaOm Radar for DSPM

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Why Enterprises Choose Sentra over Concentric

Advantage
Install in Minutes, See Value Instantly
Low Operational Cost at Petabyte Scale


AI-Powered Classification Accuracy Using Rich Context
Dynamic Coverage


Sentra
Instant Deployment, Instant Insights

Agentless and API-driven, Sentra scans data in-place with no copying—delivering insights on day one.

Built for Scale, Without the Cost

Sentra is 100–1000x more efficient, using minimal compute and bandwidth for massive-scale scanning.

Contextual Intelligence That Learns

Continuously adapts classification using rich context across data, identity, and environment.

Full Stack Coverage

Protects structured and unstructured data across IaaS, PaaS, DBaaS, SaaS, and on-prem—all from one platform.

Concentric

Data is moved out of the customer environment for scanning, adding friction and risk. Deployment can take 9–12 months in large environments.

High operational cost due to compute-heavy, inefficient architecture. Scan costs 10–100x higher than Sentra.

Limited contextual awareness; focused primarily on unstructured data with static policies.

Primarily covers unstructured data in SaaS apps; minimal visibility across cloud infrastructure and structured data.

Why Enterprises Choose Sentra over Concentric

Advantage
Install in Minutes, See Value Instantly
Low Operational Cost at Petabyte Scale


AI-Powered Classification Accuracy Using Rich Context
Dynamic Coverage


Sentra
Instant Deployment, Instant Insights

Agentless and API-driven, Sentra scans data in-place with no copying—delivering insights on day one.

Built for Scale, Without the Cost

Sentra is 100–1000x more efficient, using minimal compute and bandwidth for massive-scale scanning.

Contextual Intelligence That Learns

Continuously adapts classification using rich context across data, identity, and environment.

Full Stack Coverage

Protects structured and unstructured data across IaaS, PaaS, DBaaS, SaaS, and on-prem—all from one platform.

Concentric

Data is moved out of the customer environment for scanning, adding friction and risk. Deployment can take 9–12 months in large environments.

High operational cost due to compute-heavy, inefficient architecture. Scan costs 10–100x higher than Sentra.

Limited contextual awareness; focused primarily on unstructured data with static policies.

Primarily covers unstructured data in SaaS apps; minimal visibility across cloud infrastructure and structured data.

What Customers Are Saying About Sentra

See How Sentra Compares to Concentric in This Gartner Report
Peer insights customer choice 2025 badge
Sentra 5 star badge for highest percentage rating of any vendor
When sensitive data in our cloud data stores is duplicated or moved by engineers, we can now understand if that causes any security or compliance issues
The POC was incredible and going forward we feel this is crucial and somewhat irreplaceable for us
Agentless data classification from Sentra has been a huge help, now we can auto-classify sensitive data and prevent this data from being extracted

Learn more about Sentra's Data Security Platform

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Sentra's Data Security Platform

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Sentra's Data Security Platform

Sentra DSP empowers security teams to automatically classify sensitive data, assess risk, and remediate threats to every datastore and data asset across multiple cloud, SaaS, and on-premises environments.

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Sensitive Data Classification Challenges

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Sensitive Data Classification Challenges

At the end of the day, you need to secure your sensitive data to prevent unintended disclosure or breaches. A simple and straightforward goal.Yet, the challenge persists – how can you accurately identify the sensitive data, its sensitivity level, data subjects residency, and gain sufficient business context to understand how it's being use

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Sentra for AI & ML

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Sentra for AI & ML

Gain visibility into AI agents and their data exposure. Automatically discover AI agents, map their knowledge sources and sensitive data connections, and track user interactions to uncover hidden risks.

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