In today’s data-driven world, organizations are shifting from siloed data stacks toward intelligent, composable data platforms that support real-time analytics and AI workloads. By leveraging Spice.ai data engines, NetApp ONTAP S3 Lakehouse, and Azure NetApp Filers by Instaclustr, we can connect various data sources like Dremio, PostgreSQL, and S3 data to build a modern, performant, and cost-efficient architecture for data applications.
Seeing is believing, to watch a live demo and ask more questions, visit Will Stowe at NetApp Insight AI booth this week.
In this post, we’ll walk through how Spice.ai connects and queries multiple NetApp data sources, combines data, and uses LLM chatbots like GPT-4 to present data and answers to end users.
Spice.ai — The Data Connectors
Spice.ai provides an intelligent data layer that brings SQL and AI together. It allows developers to query data across multiple sources with sub-second latency, cache frequently used data automatically and integrate vector search and machine learning without complex pipelines. With Spice.ai, you can:
- Connect to multiple data sources (Postgres, S3, Dremio, etc.)
- Accelerate queries with smart caching
- Build APIs for real-time analytics and AI-powered applications
Dremio — The Query Acceleration Engine
Dremio acts as a data Lakehouse query platform, enabling self-service analytics without needing to move or copy data. With Dremio, you can expose NetApp S3 data as tables and join them with structured data in Postgres—without ETL. Dremio connects seamlessly to object storage and databases, providing:
- High-performance SQL queries on data lakes
- Semantic layers for business-friendly data models
- Native Apache Iceberg support for modern table formats
PostgreSQL — The Structured Backbone
PostgreSQL remains the go-to relational database for structured transactional data. Whether you’re storing user profiles, product catalogs, or reference tables, Postgres provides robust SQL capabilities and easy integration with both Dremio and Spice.ai.
Quick and easy beyond believe
Getting started with Spice.ai is incredibly straightforward. Here’s how you can set up and begin querying your data in just a few steps:
- Get started with Spice.ai in just 30 seconds: Visit Spice.ai Documentation to get started quickly.
- Configure with a powerful and easy yaml file: Below is an example.
- Run your spice.ai setup using the command: spice run
- Check SQL connection: spice sql; show tables
- Use gtp-4o with spice chat to get your question answered with data and summaries: spice chat
By combining the power of Spice.ai, Dremio, PostgreSQL, and NetApp ONTAP S3 Lakehouse, you can build a modern data platform that supports real-time analytics and AI workloads. This architecture is not only performant and scalable but also cost-efficient, making it ideal for today's data-centric applications.
Get started today and transform your data infrastructure into a powerful, intelligent platform that drives business insights and innovation.
