41 of 21.217 listings match.
Time = 5y,
src = 10/10,
lang = all,
dict = D1,
terms = 4(ANY). last watermark · 2026-05-08
Demand index · last 4 wk vs window mean
4439%
above baseline
Reg. pressure (D5 mentions)
3
across all listings in window
Top mover · D1
Postgres
∞ (z=99.0)
Recurring clusters
1
near-duplicate templates
01All 20 terms · Tools
8/20 have ≥1 citation · sparkline = trend · click row to filter · zero-count terms shown at bottom
02Term trend · top 5
anomalies marked · z > 2.5
PostgresPower BIExcelJiraDATEV
03Top movers · current half vs prev half
largest |Δ%| · z-score (Poisson)
| Term | Now | Prev | Δ % | z |
|---|---|---|---|---|
| Postgres | 25 | 0 | ∞ | 99.0 |
| Power BI | 16 | 0 | ∞ | 99.0 |
| Excel | 5 | 0 | ∞ | 99.0 |
| DATEV | 2 | 0 | ∞ | 0.0 |
| Jira | 3 | 0 | ∞ | 0.0 |
| Confluence | 1 | 0 | ∞ | 0.0 |
| Snowflake | 1 | 0 | ∞ | 0.0 |
| HubSpot | 1 | 0 | ∞ | 0.0 |
04Co-occurrence · top 20 pairs
Lift = P(A,B)/(P(A)·P(B)) · click to filter on both
| Term A | Term B | Count | Lift |
|---|---|---|---|
| Postgres | API | 5 | 1.37× |
| Postgres | integrieren | 4 | 1.31× |
| Postgres | pipeline | 4 | 1.64× |
| pipeline | API | 4 | 6.83× |
| Excel | Power BI | 3 | 1.54× |
| Power BI | analysieren | 3 | 1.92× |
| Postgres | exportieren | 3 | 1.64× |
| Postgres | DSGVO | 3 | 1.64× |
| Excel | analysieren | 2 | 4.10× |
| Power BI | automatisieren | 2 | 1.28× |
| DATEV | Postgres | 2 | 1.64× |
| analysieren | automatisieren | 2 | 5.13× |
| Excel | Jira | 2 | 5.47× |
| Jira | Power BI | 2 | 1.71× |
| Power BI | reporten | 2 | 2.56× |
| Excel | Postgres | 2 | 0.66× |
| Postgres | automatisieren | 2 | 0.82× |
| automatisieren | integrieren | 2 | 4.10× |
| Excel | Maschinenbau | 1 | 8.20× |
| Power BI | Maschinenbau | 1 | 2.56× |
05Recurring clusters · near-duplicate listings
indicates productizable workflows · click row for records
| Exemplar | Sources | Members | Median gap |
|---|---|---|---|
| Show HN: I extract recipes from TikTok, Instagram, and the messy web | Hacker | 2 | 0d |