14 of 9.726 listings match.
Time = 5y,
src = 8/8,
lang = all,
dict = D1,
terms = 3(ANY). last watermark · 2026-05-06
Demand index · last 4 wk vs window mean
1857%
above baseline
Reg. pressure (D5 mentions)
2
across all listings in window
Top mover · D1
DATEV
∞ (z=0.0)
Recurring clusters
1
near-duplicate templates
01All 20 terms · Tools
6/20 have ≥1 citation · sparkline = trend · click row to filter · zero-count terms shown at bottom
02Term trend · top 5
anomalies marked · z > 2.5
PostgresDATEVExcelHubSpotJira
03Top movers · current half vs prev half
largest |Δ%| · z-score (Poisson)
| Term | Now | Prev | Δ % | z |
|---|---|---|---|---|
| DATEV | 2 | 0 | ∞ | 0.0 |
| Postgres | 13 | 0 | ∞ | 99.0 |
| Excel | 1 | 0 | ∞ | 0.0 |
| HubSpot | 1 | 0 | ∞ | 0.0 |
| Jira | 1 | 0 | ∞ | 0.0 |
| Confluence | 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 | 6 | 1.08× |
| Postgres | pipeline | 4 | 1.08× |
| pipeline | API | 4 | 2.33× |
| Postgres | exportieren | 3 | 1.08× |
| DATEV | Postgres | 2 | 1.08× |
| Postgres | integrieren | 2 | 1.08× |
| exportieren | API | 2 | 1.56× |
| Postgres | DSGVO | 2 | 1.08× |
| DATEV | integrieren | 1 | 3.50× |
| exportieren | DSGVO | 1 | 2.33× |
| API | DSGVO | 1 | 1.17× |
| DATEV | exportieren | 1 | 2.33× |
| Excel | HubSpot | 1 | 14.00× |
| Excel | Postgres | 1 | 1.08× |
| Excel | integrieren | 1 | 7.00× |
| HubSpot | Postgres | 1 | 1.08× |
| HubSpot | integrieren | 1 | 7.00× |
| Confluence | Jira | 1 | 14.00× |
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 |