Our Platform Services
Unlock the value of your global data assets with specialized, fully-managed cloud services that scale dynamically and independently.
Cloud Data Warehousing
Run petabyte-scale SQL analytical workloads with zero performance degradation. Digitalnetinc allows you to spin up isolated Virtual Warehouses (compute clusters) to query data instantly, ensuring that workloads like sales dashboarding, financial auditing, and batch processing never compete for compute power.
Enjoy automatic scaling and auto-suspension, so compute clusters turn off when idle and boot up in milliseconds when a new query is submitted. Pay only for the exact seconds of cluster usage.
- Standard ANSI SQL Compatibility
- Multi-Cluster Warehousing
- Auto-Suspend & Auto-Resume
Unified Cloud Data Lake
Store your structured, semi-structured (JSON, Avro, Parquet, XML), and unstructured files (images, audio, PDFs) in one central place. Eliminate the complexity of managing file systems, file indexing, and metadata catalogs.
With Digitalnetinc, you don't need a separate schema design before loading data. Directly load raw JSON files and query them using SQL with our unique schema-on-read technology. This streamlines access for data analysts and data scientists alike.
- Native Semi-Structured support
- Internal & External Stages
- Automatic compression and indexing
Data Engineering
Build real-time, event-driven data ingestion pipelines. Ingest streams of IoT data, application logs, and transactional databases using NetStreams and automated ETL orchestration tools.
Write your data pipelines in the language of your choice: SQL or Python. Automated task DAGs (Directed Acyclic Graphs), dependency scheduling, and built-in error handling ensure data pipelines run continuously and recover gracefully without manual operations.
- NetStreams: In-Order Continuous Ingestion
- SQL & Python pipeline scripts
- Native Task DAG Orchestrator
AI & Machine Learning
Run complex model training, predictive analytics, and large language models (LLMs) directly within the secure data cloud boundaries. Our NetML Python runtime allows data scientists to write PySpark-style DataFrame code that translates automatically into SQL and runs on serverless warehouse nodes.
By bringing the processing logic to the data rather than extracting the data to separate compute setups, you guarantee strict security, eliminate transfer lag, and run modeling pipelines at massive scale.
- Secure Python, Java, & Scala runtimes
- Scalable model inference directly via SQL
- Native Model Registry & Versioning
Secure Data Collaboration
Instantly share datasets, schemas, and live database tables across business departments or with external clients and vendors. Traditional data sharing requires heavy file exports, FTP transfers, and API maintenance. Digitalnetinc uses live pointer sharing.
Recipients view the data in place and in real-time. Any changes updated in the primary warehouse are immediately reflected for consumers, without data copying, duplication, or additional storage billing.
- Cross-Region & Cross-Cloud sharing
- Zero data duplication / storage overhead
- Public & Private Data Marketplaces
Native Application Framework
Build and package full-stack enterprise applications that run directly inside your customer's Digitalnetinc tenant. Customers can run SaaS products, analytics tools, and dashboard interfaces without ever exposing their proprietary customer data outside their own firewall.
This breaks the traditional SaaS privacy barrier. Deploy applications natively, charge via compute credits or marketplace subscriptions, and let customers trust your code implicitly.
- Native Streamlit, Python & SQL integration
- Distributed securely through Data Marketplace
- Strict sandbox data isolation compliance
