MOSTLY AI

MOSTLY AI is a data intelligence platform for generating synthetic and mock data, analyzing data, and integrating generation into workflows. It suits teams that need synthetic relational data across several data types and deployment choices. Its breadth is balanced by substantial minimum resources for single-node Kubernetes and a Linux-only restriction on GPU support in local SDK mode.

Overview

Founded in Vienna in 2017, MOSTLY AI combines synthetic data generation with data analysis and access to production data. Its open-source Python SDK supports local generation, while the platform can also be deployed on Kubernetes or OpenShift, or installed through Minikube on a single VM. Hybrid deployment and on-premises options, including air-gapped environments, give organizations a path to keep deployment close to their own infrastructure.

Key features

The platform handles numerical, categorical, date-time, text, and geolocation data. It can synthesize relational multi-table datasets while preserving relationships between tables, a meaningful advantage when test data needs to behave like a connected database rather than a collection of unrelated rows.

Data Insights Reports, rebalancing, missing-value imputation, and generation temperature control provide ways to inspect and shape output. A natural-language assistant can create and run Python code for data analysis. These tools make the product relevant beyond data generation, though local SDK users should note that GPU support is Linux-only.

Connectors cover MySQL, PostgreSQL, MariaDB, Oracle, Microsoft SQL Server, Snowflake, Databricks, BigQuery, Apache Hive, and cloud buckets from Azure, GCP, and AWS. CSV, Parquet, and XLSX are supported formats. An API and Python client let teams integrate generation into applications and workflows.

Pricing

MOSTLY AI has a free plan at free. No further limits are stated for that plan, so it is difficult to judge its fit for sustained or high-volume use. No paid plan price is provided; organizations seeking a paid arrangement should expect custom pricing.

Platforms

MOSTLY AI is available through the web and API, with Linux and self-hosted deployment options. The SDK is an open-source Python package under the Apache v2 license and supports local synthetic data generation. For local SDK GPU acceleration, Linux is required.

Infrastructure requirements are significant for a single-node Kubernetes deployment: at least 24 CPU cores, 48 GB of RAM, and 256 GB of storage. That makes the deployment a more natural fit for well-provisioned environments than for small teams with limited infrastructure. Kubernetes, OpenShift, and Minikube are deployment paths; support is available by email.

Who it's for

MOSTLY AI is best suited to organizations that need realistic synthetic data across related tables, want analysis and generation in one platform, or require self-hosted, private-cloud, or air-gapped deployment. Teams integrating generation into software can use its API and Python client. It is less compelling for a small local setup that depends on GPU acceleration outside Linux, or for teams unable to meet the Kubernetes resource floor.

Pros and cons

Pros

• Relational synthesis: Preserving links across tables better serves database testing than generating disconnected records.
• Broad data coverage: Support for structured fields, text, and geolocation, along with CSV, Parquet, and XLSX, accommodates varied data workflows.
• Deployment flexibility: Kubernetes, OpenShift, local SDK generation, on-premises, air-gapped, and private-cloud options address different infrastructure and control needs.
• Workflow integration: API and Python client support let teams incorporate generation into applications rather than rely only on manual exports.

Cons

• High Kubernetes baseline: A single-node deployment starts at 24 CPU cores, 48 GB RAM, and 256 GB storage, a substantial commitment for smaller environments.
• Linux-only local GPU support: SDK users on other operating systems cannot use GPU support in local mode.
• Unclear free-plan ceiling: The free plan is listed as free, but without stated caps, buyers cannot readily assess whether it will cover ongoing needs.

Alternatives

Choose Windocks if a free option with stated database image and container limits, Windows support, and no support is a better match. Metasyn is a free, MIT-licensed open-source Python package for teams seeking a package rather than a broader platform. Tonic Fabricate offers a free plan with monthly credits and basic exports, plus a paid Plus tier.

Mockaroo may suit users whose needs fit its free limits of 1,000 rows per file and 200 API requests per day. Synthetic Data Vault offers a free community plan with five data types, five basic constraints, and nine models. BlazeMeter is another freemium option, with an APIs Small plan priced at $79 a month.

Curiosity Software Enterprise Test Data is an enterprise test-data option with custom quote pricing charged by data type rather than volume. Perforce Delphix Test Data Management is an enterprise test data management platform with custom pricing.

For broader comparisons, see Test Data Management Software, Test Data Generation Tools, AI Synthetic Data Generators, Synthetic Data Generation Software, and Data Masking Software.

Verdict

MOSTLY AI is a strong choice for teams that need relational synthetic data, flexible deployment, and analysis and integration tools in one platform. The decisive reasons to look elsewhere are the high single-node Kubernetes resource floor and Linux-only GPU support in local SDK mode; buyers should also confirm that the free plan’s limits fit their intended workload.