This is the Data Ecosystem Wiki — an attempt to write down, in one place and in plain English, what every important tool in the modern data stack actually is, where it came from, and how it relates to everything else. It's maintained by TextQL, and it's organized around the structure of the stack itself.

This page explains how the wiki is laid out, what conventions it follows, and how to find what you need.

What This Wiki Is

A few things, plainly:

• An encyclopedia, not a tutorial. Each page is meant to be a self-contained reference that explains a tool, a category, or a concept well enough that you can read it once and understand the thing.
• Opinionated, not neutral. The data infrastructure space is full of vendor marketing pretending to be objective. This wiki has takes. We try to be fair, but we tell you what we think.
• Historical, not just current. We care about origin stories. Knowing why a tool exists — what problem its founders saw, what came before it, what it killed — usually tells you more about whether it's right for you than any feature list.
• Cross-referenced, not siloed. Every page links generously to adjacent tools, alternative vendors, and related concepts, so you can wander your way to the answer rather than having to search for it.

What This Wiki Is Not

• Not vendor documentation. If you want to know how to configure Snowflake's Time Travel, go to Snowflake's docs. If you want to know what Time Travel is, why it exists, and how it compares to Iceberg snapshots, this is the right place.
• Not a buyer's guide in the lead-gen sense. We don't have a "request a demo" button on every page. We do have opinions about what we think is winning, what is losing, and what is overrated.
• Not exhaustive. There are thousands of tools in the data ecosystem. We cover the ones that matter for understanding how the stack works in 2026. If something is missing, it's either too small, too dead, or too narrow to fit the wiki's scope.

How Pages Are Organized

Pages fall into three types:

### Category overview pages

These are the index pages for each layer of the stack — Data Warehouses, Reverse ETL, Data Workspaces, and so on. They explain:

• What the category is, in plain English.
• Where it came from historically.
• What makes a tool "in" the category vs. adjacent.
• The opinionated take on which vendors are winning and why.
• Where the layer fits in the broader stack.
• A list of the major vendors covered in the wiki.

If you're new to a category, start here.

### Individual vendor / product pages

These are the pages for specific tools — Snowflake, Hightouch, Hex. They follow a consistent structure:

• An infobox at the top with founding year, founders, HQ, category, and key facts.
• A What it actually is section — the plain-English explanation of what the product does.
• An origin story — who founded it, when, why, and what they were reacting against.
• An opinionated take — our view of why this tool is winning, losing, or holding steady, and what its real strategic position is.
• A stack fit section — where in the data stack the tool sits and what it connects to.
• A TextQL fit section — how TextQL works with the tool (since this wiki is maintained by TextQL, we are transparent about that).
• A See Also block of related links at the bottom.

### Concept pages

A few pages cover concepts that aren't a single tool: Stack Overview, Data Lakehouse, Semantic Layer. These follow the same general structure but emphasize the idea over any specific vendor.

Conventions You'll See

• Bold is used for the first mention of a tool name and for terms we want you to remember.
• Italics is used for emphasis and for the names of papers, books, and product features.
• Internal links use the wiki's canonical paths (e.g., /data-warehouses/snowflake) so they keep working as the wiki grows.
• Every page ends with a `