Anchors
| Anchor text | Ref. domains ▾ | Top DR | Ref. pages | Links to target | Dofollow links |
|---|---|---|---|---|---|
| Simon Späti | 3 | — | 0 | 8 | 8 100% |
| A Diary of a Data Engineer | 2 | — | 0 | 2 | 1 50% |
| Second Brain | 2 | — | 0 | 2 | 0 0% |
| My Obsidian note-taking workflow | 2 | — | 0 | 2 | 2 100% |
| open | 2 | — | 0 | 2 | 2 100% |
| Why Vim Is More than Just an Editor – Vim Language, Motions, and Modes Explained | 2 | — | 0 | 2 | 0 0% |
| many setups | 1 | — | 0 | 1 | 0 0% |
| Discover the Joy of Self-Hosting and Tech Independence | 1 | — | 0 | 1 | 1 100% |
| | 1 | — | 0 | 1 | 1 100% |
| The Open Table Format Revolution: Why Hyperscalers Are Betting on Managed Iceberg | ssp.sh | 1 | — | 0 | 1 | 1 100% |
| Normalization | 1 | — | 0 | 1 | 1 100% |
| Obsidian workflow | 1 | — | 0 | 1 | 0 0% |
| Jinja Template | 1 | — | 0 | 1 | 1 100% |
| Closed-Source Data Platforms | 1 | — | 0 | 1 | 1 100% |
| Data Warehouse Automation (DWA) – Series | 1 | — | 0 | 1 | 1 100% |
| curated list | 1 | — | 0 | 1 | 1 100% |
| post | 1 | — | 0 | 1 | 1 100% |
| metrics | 1 | — | 0 | 1 | 1 100% |
| Slowly Changing Dimension | 1 | — | 0 | 1 | 1 100% |
| PKM workflow | 1 | — | 0 | 1 | 0 0% |
| One Big Table | 1 | — | 0 | 1 | 1 100% |
| Semantic Layer | 1 | — | 0 | 1 | 1 100% |
| Ibis | 1 | — | 0 | 1 | 1 100% |
| Public Second Brain article on ssp.sh | 1 | — | 0 | 1 | 1 100% |
| Slowly Changing Dimension (Type 2) | 1 | — | 0 | 5 | 5 100% |
| vim workflow | 1 | — | 0 | 1 | 0 0% |
| GenBI | 1 | — | 0 | 1 | 1 100% |
| Parametric Data Pipeline | 1 | — | 0 | 1 | 1 100% |
| Summer Data Engineering Roadmap | 1 | — | 0 | 2 | 2 100% |
| More Images | 1 | — | 0 | 1 | 0 0% |
| data modeling languages | 1 | — | 0 | 1 | 1 100% |
| kiiro | 1 | — | 0 | 1 | 1 100% |
| Data Vault | 1 | — | 0 | 1 | 1 100% |
| Obsidian | 1 | — | 0 | 2 | 0 0% |
| Data Catalog | 1 | — | 0 | 1 | 1 100% |
| Microservices | 1 | — | 0 | 1 | 1 100% |
| open standards | 1 | — | 0 | 1 | 1 100% |
| Self-Serve BI | 1 | — | 0 | 1 | 1 100% |
| Factory Pattern | 1 | — | 0 | 1 | 1 100% |
| functional data engineering | 1 | — | 0 | 4 | 4 100% |
| Master Data Management | 1 | — | 0 | 1 | 1 100% |
| imperative | 1 | — | 0 | 4 | 4 100% |
| ssp.sh | 1 | — | 0 | 1 | 0 0% |
| Cloud Data Platforms | 1 | — | 0 | 1 | 1 100% |
| real-time analytics databases | 1 | — | 0 | 1 | 1 100% |
| Apache Arrow | 1 | — | 0 | 1 | 1 100% |
| Data Engineering Vault | 1 | — | 0 | 1 | 1 100% |
| Metrics Layer | 1 | — | 0 | 1 | 1 100% |
| data assets | 1 | — | 0 | 1 | 1 100% |
| Data Warehouse Automation | 1 | — | 0 | 1 | 1 100% |
Frequently Asked Questions
What anchor texts are used to link to ssp.sh?
This page shows all anchor texts found in backlinks pointing to ssp.sh, sorted by the number of referring domains using each anchor. Anchor texts range from branded terms (like the domain name itself) to keyword-rich phrases that describe the linked content. The distribution of anchor texts reveals how other websites perceive and describe ssp.sh.
What is anchor text?
Anchor text is the visible, clickable text in a hyperlink. Search engines use anchor text as a signal to understand what the linked page is about. For example, if many sites link to a page using the anchor text "best running shoes," search engines infer that the page is relevant to that topic. Anchor text appears in several forms: exact-match (contains target keywords), branded (uses the company or domain name), generic (like "click here"), and naked URLs.
Why is anchor text analysis important for SEO?
Anchor text analysis helps identify potential SEO risks and opportunities. A natural backlink profile has diverse anchor texts including branded terms, generic phrases, and topic-relevant keywords. Over-optimization, where too many backlinks use the same exact-match keyword anchor, can trigger search engine penalties. Conversely, understanding which anchors drive the most authority (measured by referring domain count and DR) helps prioritize link building efforts.
How many unique anchor texts does ssp.sh have?
The anchor text report for ssp.sh displays all distinct anchor texts grouped by their hash. Each row shows how many unique referring domains use that anchor, the total number of links, and the dofollow percentage. A high number of unique anchors generally indicates a healthy, natural backlink profile with diverse link sources.