Mage Data Test Data Management vs MOSTLY AI
Mage Data Test Data Management
magedata.ai
MOSTLY AI
mostly.aiSide by side
| Figure | Mage Data Test Data Management | MOSTLY AI |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Test Data Management Software | 7.3 (#18) | 7.7 (#11) |
| Company history | Mage Data's CEO profile says Rajesh K. Parthasarathy founded MENTIS in 2004; the profile does not state that Mage Data itself was founded that year. | MOSTLY AI says it was founded in 2017 in Vienna, Austria. |
| Deployment | Mage Data says the platform is installed in the customer's environment on-premises, in their cloud account, or in a hybrid deployment, and is not a SaaS service. | The platform can be deployed on Kubernetes or OpenShift, or installed via Minikube on a single VM. |
| Founded | 2004 | 2017 |
| Integrations | Mage Data lists Jenkins, GitLab CI, GitHub Actions, and Azure DevOps Pipelines as CI/CD integrations, and says any orchestrator that can call a REST API can connect. | Listed connectors include MySQL, PostgreSQL, MariaDB, Oracle, MS SQL Server, Snowflake, Databricks, BigQuery, and Azure, GCP, and AWS cloud buckets. |
| Support | Mage Data says its contact team will respond within one business day to discuss requirements or arrange a personalized demo. | Users can contact support by emailing [email protected]. |
Plans
Mage Data Test Data Management
- Test Data ManagementPriced on request
In their own words
Mage Data Test Data Management
Mage Data Test Data Management has no write-up on Specifiction yet; its figures are above.
MOSTLY AI
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.