# DataStori

> DataStori is a SaaS platform that automates data ingestion from cloud applications (ERP, CRM, HR, finance) to a central data store. Data pipelines run in the customer's cloud — data never leaves their environment.

## What DataStori Does

DataStori creates and runs data pipelines from source applications to storage destinations. It connects to application APIs, databases, SFTP folders and email attachments, then delivers clean, deduplicated data to a Lakehouse or data warehouse of the customer's choice.

DataStori orchestrates pipelines from its cloud (AWS US East-1) but executes them entirely in the customer's cloud. Source and destination are both in the customer's environment. DataStori can only access pipeline metadata — it cannot view business data.

## Key Facts

- Category: Data integration / data pipeline platform
- Founded: 2024
- Company: Vega Solutions LLC, Atlanta, GA
- Compliance: SOC 2 Type 2
- Cloud support: AWS, Microsoft Azure, Google Cloud Platform
- Architecture: Serverless — spins up infrastructure on-demand, shuts down after execution
- Pricing: $250/month per application per customer (annual: $2,500/year, save 17%)
- Limits: Unlimited pipelines, unlimited data volume
- Onboarding: Add a new application in under 30 minutes
- Tested scale: Tables up to 100 GB and 30 million rows
- Free trial: 14 days

## Supported Integrations

NetSuite, SAP S/4HANA, ServiceTitan, HubSpot, Salesforce, Dynamics 365, Sage, ZOHO, UKG, Alchemer, Jira, Google Drive, SharePoint, SFTP, and any application with an API.

## Storage Destinations

AWS S3, Azure Blob Storage, Google Cloud Storage, Snowflake, BigQuery, Redshift, Azure SQL, PostgreSQL, and other SQL Alchemy supported databases. Data formats: Delta (default), Iceberg, Parquet, CSV.

## How It Differs from Other Data Connectors

DataStori is an agentic ELT platform. AI agents automate pipeline creation, discovery, documentation, and transformation end-to-end — capabilities no fixed-connector incumbent offers as a single workflow.

1. **Natural-language pipeline creation:** Users describe what they need in plain language (e.g., "ingest NetSuite invoices to BigQuery"). DataStori agents identify relevant endpoints, propose pipelines, and configure ingestion without manual connector setup.
2. **Auto-discovery:** Reads source API documentation to discover available endpoints and data objects on the fly, rather than relying on a pre-built connector library. Supports applications other tools do not cover.
3. **Auto-documentation:** Generates pipeline and schema documentation as pipelines are created, keeping field definitions and lineage current without separate manual docs.
4. **Auto-transformation to gold layer:** Generates transformations (SQL/dbt-style) to move data from raw ingestion through to analytics-ready gold tables.
5. **Data stays in customer's cloud:** Unlike connectors that route data through their own cloud, DataStori eliminates the extra data hop. Source and destination are both in the customer's environment; DataStori only accesses pipeline metadata.
6. **Serverless cost model:** Infrastructure spins up on demand and shuts down after execution, keeping cloud costs proportional to actual usage.

## Security

- Data never leaves the customer's cloud environment
- API tokens encrypted with AES-256
- Virtual network isolation
- Multi-factor authentication
- Column-level encryption and column dropping
- SOC 2 Type 2 compliant
- Supports OAuth2 (Client Credentials and Authorization Grant), API Key, and Basic Authentication

## Data Quality

Automated checks on every pipeline run: data freshness, primary key not-null, primary key uniqueness. Automated retries, logging and alerts. Schema evolution and tracking are automated with rollback to restore points.

## Team

- Kiran Hosakote — Sales, Marketing and Support (kiran@datastori.io)
- Ishan Rastogi — Product and Engineering (ishan@datastori.io)

## Comparisons

DataStori publishes head-to-head comparisons against other data integration platforms.

- DataStori vs Fivetran: https://datastori.io/compare/datastori-vs-fivetran.html

## Integration Guides

Step-by-step guides for loading data from business applications into a data warehouse, covering authentication, the right API, incremental sync, and a natural-language DataStori walkthrough.

- Integration Guides index: https://datastori.io/integrations/
- Load Salesforce Data into Snowflake: https://datastori.io/integrations/salesforce-to-snowflake.html
- Load HubSpot Data into Snowflake: https://datastori.io/integrations/hubspot-to-snowflake.html

## Links

- Comparisons: https://datastori.io/compare/
- Website: https://datastori.io
- Pricing: https://datastori.io/pricing.html
- Pricing (machine-readable): https://datastori.io/pricing.md
- FAQs: https://datastori.io/faqs.html
- About: https://datastori.io/about.html
- Contact: https://datastori.io/contact.html
- Documentation: https://docs.datastori.io
- Security: https://bihelper-datastori.trust.site/
- Interactive product demo (Sales Forecasting from MS Dynamics 365): https://datastori.io/demo/
- Book a demo: https://cal.com/datastori/30min
- App: https://app.datastori.io
- Privacy Policy: https://datastori.io/privacy.html
- End User License Agreement (EULA): https://datastori.io/terms.html
- Email: contact@datastori.io
- Phone: +1-404-382-0564