DATPROF vs MOSTLY AI

DATPROF is a test data management platform for creating, protecting, automating and delivering data for development, testing and QA. Its modules cover privacy, subsetting, runtime, analysis and virtualization. Privacy masks test data and creates synthetic data while retaining representative characteristics, with more than 50 built-in generators supporting different languages. Subset extracts selected production data for test environments while preserving relationships. Runtime supports self-service provisioning, scheduling, monitoring and REST API automation. DATPROF can be deployed on premise or in the cloud, and says data stays in its database domains during masking. Native database support includes Oracle, Microsoft SQL Server, DB2 iSeries, DB2 LUW, PostgreSQL, EDB, MySQL and MariaDB. Supported flat file formats include CSV, Fixed Length, Recursive Fixed Length and XML. DATPROF says its masking can support GDPR, PCI and HIPAA requirements. Its security program aligns with ISO 27001 principles and includes SAST, dependency scanning and DAST in development. Support is available through a service desk portal, email and a documentation knowledge base. Pricing is available on request, and a free trial is listed.

MOSTLY AI is a data intelligence platform for accessing production data, generating synthetic, mock and simulated data, and analyzing data. Its assistant lets users request Python code in natural language and run it for analysis. The open-source Synthetic Data SDK supports local generation and uses the Apache v2 license. The platform handles numerical, categorical, date-time, text and geolocation data; it can synthesize relational tables while preserving their relationships. Other controls include Data Insights Reports, data rebalancing, missing-value imputation and generation temperature settings. Listed database connectors include MySQL, PostgreSQL, MariaDB, Oracle, Microsoft SQL Server, Snowflake, Databricks, BigQuery and Apache Hive; cloud bucket connectors include Azure, GCP and AWS. An API and Python client support integration into applications and workflows. Deployment options include Kubernetes, OpenShift and Minikube, as well as on-premises, private-cloud and air-gapped installations. The maker says the platform is SOC 2 and ISO 27001 certified. A single-node Kubernetes deployment requires at least 24 CPU cores, 48 GB RAM and 256 GB storage. The free plan is free, with no further limits stated. It is available via API, Linux, self-hosting and web.