400 of 19.850 listings match.
Time = 5y,
src = 10/10,
lang = all,
dict = D1,
terms = 7(ANY). last watermark · 2026-05-07
Demand index · last 4 wk vs window mean
5525%
above baseline
Reg. pressure (D5 mentions)
6
across all listings in window
Top mover · D1
Postgres
∞ (z=99.0)
Recurring clusters
8
near-duplicate templates
01All 20 terms · Tools
14/20 have ≥1 citation · sparkline = trend · click row to filter · zero-count terms shown at bottom
02Term trend · top 5
anomalies marked · z > 2.5
SAPsevdeskPostgresDATEVBigQuery
03Top movers · current half vs prev half
largest |Δ%| · z-score (Poisson)
| Term | Now | Prev | Δ % | z |
|---|---|---|---|---|
| Postgres | 24 | 0 | ∞ | 99.0 |
| DATEV | 4 | 0 | ∞ | 99.0 |
| sevdesk | 39 | 0 | ∞ | 99.0 |
| MS Dynamics | 1 | 0 | ∞ | 0.0 |
| Excel | 2 | 0 | ∞ | 0.0 |
| Snowflake | 2 | 0 | ∞ | 0.0 |
| BigQuery | 4 | 0 | ∞ | 99.0 |
| Lexoffice | 2 | 0 | ∞ | 0.0 |
| Tableau | 1 | 0 | ∞ | 0.0 |
| Looker | 1 | 0 | ∞ | 0.0 |
| Metabase | 1 | 0 | ∞ | 0.0 |
| Lexware | 1 | 0 | ∞ | 0.0 |
| HubSpot | 1 | 0 | ∞ | 0.0 |
| SAP | 332 | 1 | +33100.0% | 331.0 |
04Co-occurrence · top 20 pairs
Lift = P(A,B)/(P(A)·P(B)) · click to filter on both
| Term A | Term B | Count | Lift |
|---|---|---|---|
| sevdesk | API | 14 | 5.13× |
| SAP | API | 9 | 0.39× |
| SAP | migrieren | 7 | 1.20× |
| SAP | integrieren | 5 | 0.60× |
| Postgres | API | 5 | 2.98× |
| Postgres | integrieren | 4 | 6.67× |
| Postgres | pipeline | 4 | 13.33× |
| pipeline | API | 4 | 11.43× |
| DATEV | exportieren | 3 | 37.50× |
| sevdesk | exportieren | 3 | 3.85× |
| Postgres | exportieren | 3 | 6.25× |
| Postgres | DSGVO | 3 | 12.50× |
| DATEV | sevdesk | 2 | 5.13× |
| SAP | Logistik | 2 | 1.20× |
| SAP | analysieren | 2 | 0.80× |
| analysieren | integrieren | 2 | 26.67× |
| integrieren | Schnittstelle | 2 | 40.00× |
| DATEV | Postgres | 2 | 8.33× |
| SAP | reporten | 2 | 0.80× |
| BigQuery | Snowflake | 2 | 100.00× |
05Recurring clusters · near-duplicate listings
indicates productizable workflows · click row for records