Aurva Database Activity Monitoring vs Greenmask

Aurva Database Activity Monitoring is a paid, self-hosted product for monitoring database queries from people, service accounts, and AI agents. It identifies the responsible actor and shows role, application, and access path. For AI agents, it builds behavioral baselines and alerts when activity deviates from expected patterns. Policies can govern access by identity, data sensitivity, location, and time, including blocking access or redacting columns. Aurva describes a passive, out-of-band architecture that monitors traffic without sitting in the query path and says it adds 0 ms of application latency. Deployment options include agent, agentless, combined, cloud, on-premises, and hybrid setups. Named coverage includes PostgreSQL, MySQL, MongoDB, Snowflake, BigQuery, DynamoDB, Kafka, and other stores, with integrations including Databricks, Amazon Athena, Aurora, Redis, and Microsoft SQL Server. Aurva lists audit logging and sensitive-data monitoring aligned with SOC 2 and ISO 27001 objectives. Pricing is custom and available on request.

Greenmask is a free, open-source utility for logical database backups, anonymization, synthetic data generation, and restoration. It currently supports PostgreSQL, with MySQL, MongoDB, and other database support in development. Transformations can be deterministic or random, use dynamic parameters, mask data, or apply custom rules based on domains. Configuration validation can show warnings and data or schema differences, and transformation settings can be inherited across partitions of partitioned tables. Greenmask stores backups in local directories or S3-like remote storage. It supports parallel dumping and restoration, as well as parallel compression with pgzip. Its logical-dump approach does not require changes to the existing database schema, and dumps can be restored with pg_restore. CI/CD integration can automate anonymization and restoration. Greenmask runs on Linux and macOS and can be self-hosted on premises. Installation options include an install script, Docker, Homebrew, or building from source; the install script works on Linux and macOS, while Windows is not supported yet. A Docker Playground with sample databases provides a sandbox for trying the utility. The maker offers paid custom development for urgent or enterprise-specific feature requests.