Natural Language to SQL

Why on Shakudo

Simple, Fast, and Powerful

Shakudo offers the fastest way to self-serve the best-in-class LLM systems and vector databases. Set up and start using your data and AI stack components in minutes.

Security and Production-Ready Endpoints

Shakudo keeps your data secure and inside your existing infrastructure — your data will not be used in any form.

Efficient Data Processing Pipeline and Tools for Real-Time Data Ingestion

Shakudo pipeline jobs use best-in-class stack components to keep your vector databases refreshed.

Language to SQL Is Only One Piece of the Puzzle

Growth-Ready Infrastructure

Scale

Ensures compatibility with expanding operations through Kubernetes-based scalability.
Maintains performance stability during high demand as your company grows.
Accommodates increasing workload volumes through flexible resource management.

Comprehensive Tooling

Complete

Integrates with over 116 pre-configured data stack components for diverse business needs.
Automates cloud infrastructure setup and maintenance, simplifying data scientists' workflow.
Delivers pre-built patterns for common ML tasks, streamlining development and deployment processes.

Streamlined Operations

Efficiency

Enables quick access to GPUs for faster ML model training.
Provides an intuitive single pane UI, making advanced data science tasks more accessible.
Facilitates seamless collaboration and consistent environments, cutting down on project timelines.

Language to SQL FAQs

Common Questions

Can I integrate legacy system data with modern data platforms?

Absolutely! Tools like Airbyte are designed to bridge the gap between old-school databases and modern data ecosystems. They allow you to pull data from legacy systems and seamlessly integrate it with newer data platforms, ensuring you don’t miss out on leveraging historical data for contemporary analytics.

What is the best way to gather data from multiple sources?

To gather data from multiple sources, you can use tools like Airbyte and n8n. These tools ensure that data from various sources are collected consistently and efficiently, whether it's for bulk data integration for ETL or custom workflow automation for business processes.

What is natural language querying, and how does it simplify data analysis?

Natural language querying allows users to perform data searches and generate reports using everyday language instead of complex query syntax. This approach makes data analytics accessible to non-technical users, democratizing data insights.

What are n8n workflow templates, and how do they assist in business process automation?

n8n workflow templates are pre-designed frameworks that help automate and optimize business processes. They allow users to integrate and automate tasks across different applications and data sources without extensive coding.

What is data integration and why is it important?

Data integration involves combining data from different sources to create a unified view. This process is essential for businesses to gain comprehensive insights, make informed decisions, and streamline operations.

How quickly can I get started with deploying models on Shakudo?

You can get started almost immediately. Shakudo's user-friendly interface and extensive documentation mean that setting up and deploying your models can be done with minimal setup time.

What kind of support can I expect from Shakudo?

Shakudo offers robust support options including a comprehensive knowledge base, 24/7/365 live support for critical issues, and dedicated account management to ensure you get the most out of the platform.

How can AI help me access my data more easily without compromising security?

AI technologies, specifically Large Language Models hosted on your own infrastructure, can process and analyze data securely by keeping all interactions internal. This setup allows you to use natural language to query data, making access straightforward while maintaining strict data security.

How does Shakudo enable querying data with natural language?

Shakudo allows users to describe their data needs in natural language. It then automatically converts these descriptions into SQL queries using large language models host on your infrastructure facilitating quick and easy data retrieval without the need for SQL knowledge.

Can you explain how DataHub enriches data with metadata?

DataHub is a metadata platform that enhances data management by adding descriptive, structural, and administrative metadata to your data assets. This helps users in identifying the lineage, ownership, and usage of data, thereby improving trust and clarity.

What is metadata and why is it important for my data?

Metadata is data that provides information about other data. It makes data more discoverable and understandable by detailing its origin, meaning, and relationships to other data. Tools like DataHub enrich your data environment with metadata, helping users and systems effectively find and utilize data assets.

How can Airbyte help in data integration?

Airbyte is a tool that facilitates bulk data integration for ETL (Extract, Transform, Load) processes. It supports syncing data from various sources to your databases, lakes, or warehouses seamlessly, ensuring data consistency and accessibility.

How can I ensure my data remains secure while using Shakudo?

Security is a top priority at Shakudo. Your data belongs on your cloud — that’s why Shakudo can be easily deployed on any cloud or your on-prem infrastructure.

Can Shakudo handle large-scale machine learning projects?

Yes, Shakudo is built for scale. Thanks to its underlying Kubernetes architecture and scalable components, it can handle large-scale machine learning projects with ease, providing the necessary resources as your project grows.

Write Natural Language Queries Instead of SQL

Step 1

Gather Data from Multiple Sources

Step 2

Take Control of your Data

Step 3

Discover and Query the Data with Natural Language