Pricing Built
for Companies
of All Sizes
Modern’s customer-first approach applies to our pricing too. It is an extension of our product philosophy where the focus is on finding value in data through activation rather than moving or storing it.
Customer First Pricing
To ensure our customers find value with DataOS we have two kinds of pricing models available to our customers.
01. Pay as You Go
Get started with no upfront fees. With pay-per-use, you pay for data’s value, not just to process it.
02. Enterprise
For enterprises with high volumes of usage, a yearly subscription with no limits on usage and functionality.
Learn more about pricing.
Key Features
Observability
Monitor the health and performance of your data and enhance data reliability
Data Depot
Connect data sources to DataOS and start gaining value without moving any data
Data as Software
Use and deploy data as software with versioning capabilities, including data replay
Data Quality
Ensure trustworthy data and high-quality insights with validation and profiling checks
Data as a Product
Convert raw data into consumable data products with dictionary, schema evolution, lineage, impact, profiling, usage, and quality
Data Sharing
Enable seamless, secure, and monitored data collaboration across your business ecosystem to unlock new business models and insights
Knowledge Graph
A semantic network that is enriched in real-time with metadata and lineage to reflect the complex relationships between various data sets
Icebase
Built-in lakehouse that delivers ACID compliance, reliability, and performance for both structured and unstructured data
Governance
Automate data access control with granular privacy controls — ABAC governance enables flexible and scalable policies that adapt to changing or new compliance regulations
Workbench
A fast, distributed SQL query engine for big data analytics providing low code access to data and insights for business users — a data GUI for everyone to use
Automatic Data Catalog
Automatic cataloging of all data with real-time updates so that teams discover deep connections, uncover patterns within the data, and get definitive explainable results