> For the complete documentation index, see [llms.txt](https://docs.e6data.com/query-engine/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.e6data.com/query-engine/get-started/readme.md).

# Introduction to e6 Query Engine

## What is e6 Query Engine?

e6 Query Engine is a lakehouse compute engine for data teams who need fast, cost-efficient analytics directly on their data lake. It runs SQL and AI workloads against your existing storage - S3, ADLS Gen2, or Iceberg-managed data - without copying data into a separate warehouse.

It is designed for the three things that make modern analytics hard:

* **High concurrency** - many users running many queries at the same time.
* **Complex SQL** - joins, window functions, and aggregations over large fact tables.
* **Cost discipline** - paying for what you actually use, not for idle infrastructure.

## How customers use e6 Query Engine

* **BI dashboards** at the scale of thousands of concurrent users, with sub-second query times.
* **Operational analytics** for product, ops, and revenue teams that need fresh answers, not warehouse refresh cycles.
* **Ad-hoc exploration** on data lakes too large to load into a traditional warehouse.
* **AI/ML feature pipelines** running close to the data.

## Getting Started

Everything you need to start querying with e6data - from understanding the platform to running your first query.

[**Architecture**](/query-engine/get-started/architecture.md) - Understand e6data's query engine architecture, key constructs, and supported deployment models.

[**Identity and access setup**](/query-engine/get-started/identity-access-setup/sign-up-and-login.md) - Sign up, log in, set up your organization, and invite your team.

[**Deployment models**](/query-engine/get-started/deployment-models.md) **-** Two ways to run e6 Query Engine, both keeping your data in your cloud:

* **Serverless** - e6 Query Engine manages the compute infrastructure. Fastest to get started.
* **In Your VPC** - compute runs inside your own Kubernetes cluster. Useful when network isolation is a hard requirement.

[**Quickstart**](/query-engine/get-started/quickstart.md) - your first end-to-end query, or jump straight to [Deployment](/query-engine/guides/deployment/aws-serverless.md) for your cloud.

## Where to ask questions

* FAQs for your deployment path: [AWS Serverless](/query-engine/guides/deployment/aws-serverless/faqs.md), [AWS In-VPC / CloudPrem](/query-engine/guides/deployment/aws-in-vpc/faqs.md), or [Azure Serverless](/query-engine/guides/deployment/azure-serverless/faqs.md).
* Contact your e6data CSM or support engineer for setup-specific questions.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.e6data.com/query-engine/get-started/readme.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
