AI Tech Secure Database Security vs Satori Data Security Platform

AI Tech Secure Database Security monitors database activity, identifies SAP-aware bypass patterns, and masks sensitive information. Live monitoring covers direct SQL changes, exports, privileged access, and bypass activity. The product lists 21 pre-built monitoring rules mapped to SOX, GDPR, HIPAA, PCI DSS, and 21 CFR Part 11. In SAP environments, database changes can be correlated with SAP T-codes and CDHDR/CDPOS change documents. Masking supports query-time dynamic protection and static masked copies for development, QA, and UAT. Listed controls include role-based policies, PII and PHI field catalogs, and a masking audit trail. Alerts include exports, bulk access, severity-based escalation, and SIEM integration readiness. Named databases are SAP HANA, Oracle, SQL Server, PostgreSQL, and Snowflake, with additional platforms through the Connector Factory. Deployment is hybrid, and audit reporting and threat detection are listed capabilities. Pricing is on request through a direct B2B sales process.

Satori Data Security Platform helps security and engineering teams control access to data across multi-cloud and on-premises environments, from production systems to AI. It discovers and classifies data assets, including sensitive data, and monitors data stores and AI applications for security. Centralized controls provide visibility into potential access, while real-time enforcement applies access and security policies. The platform can map and monitor exposure risks and automate responses. It covers databases, data lakes, and data warehouses, with integrations including Snowflake, Databricks, Amazon Redshift, PostgreSQL, Amazon S3, Microsoft SQL Server, GraphQL, and Microsoft Fabric. Deployment can be Satori-managed SaaS, dedicated private SaaS, or customer-hosted in a Kubernetes cluster on AWS, Azure, or GCP. Satori describes its architecture as cloud-native and Kubernetes-based, with horizontal scalability and fault tolerance. It states a 99.99% uptime SLA and millisecond-scale added latency, and says implementation requires no changes to data, schema, or user interactions. Pricing is on request; the pricing page asks visitors to submit a form rather than listing plan prices.