300 of 19.280 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
5590%
above baseline
Reg. pressure (D5 mentions)
6
across all listings in window
Top mover · D1
Snowflake
∞ (z=99.0)
Recurring clusters
6
near-duplicate templates
01All 20 terms · Tools
12/20 have ≥1 citation · sparkline = trend · click row to filter · zero-count terms shown at bottom
02Term trend · top 5
anomalies marked · z > 2.5
SAPPostgresSnowflakeHubSpotBigQuery
03Top movers · current half vs prev half
largest |Δ%| · z-score (Poisson)
| Term | Now | Prev | Δ % | z |
|---|---|---|---|---|
| Snowflake | 20 | 0 | ∞ | 99.0 |
| Postgres | 23 | 0 | ∞ | 99.0 |
| HubSpot | 16 | 0 | ∞ | 99.0 |
| DATEV | 2 | 0 | ∞ | 0.0 |
| Excel | 3 | 0 | ∞ | 0.0 |
| MS Dynamics | 1 | 0 | ∞ | 0.0 |
| BigQuery | 4 | 0 | ∞ | 99.0 |
| Salesforce | 2 | 0 | ∞ | 0.0 |
| Tableau | 1 | 0 | ∞ | 0.0 |
| Looker | 1 | 0 | ∞ | 0.0 |
| Metabase | 1 | 0 | ∞ | 0.0 |
| SAP | 239 | 1 | +23800.0% | 238.0 |
04Co-occurrence · top 20 pairs
Lift = P(A,B)/(P(A)·P(B)) · click to filter on both
| Term A | Term B | Count | Lift |
|---|---|---|---|
| SAP | API | 9 | 0.75× |
| Postgres | API | 5 | 4.35× |
| Postgres | integrieren | 4 | 5.80× |
| Postgres | pipeline | 4 | 6.52× |
| pipeline | API | 4 | 10.00× |
| SAP | integrieren | 3 | 0.42× |
| HubSpot | integrieren | 3 | 6.25× |
| HubSpot | pipeline | 3 | 7.03× |
| Postgres | exportieren | 3 | 7.83× |
| Postgres | DSGVO | 3 | 9.78× |
| SAP | analysieren | 2 | 0.83× |
| analysieren | integrieren | 2 | 22.22× |
| integrieren | Schnittstelle | 2 | 33.33× |
| DATEV | Postgres | 2 | 13.04× |
| Excel | HubSpot | 2 | 12.50× |
| HubSpot | automate | 2 | 18.75× |
| automate | pipeline | 2 | 37.50× |
| BigQuery | Snowflake | 2 | 7.50× |
| HubSpot | Salesforce | 2 | 18.75× |
| Postgres | automatisieren | 2 | 8.70× |
05Recurring clusters · near-duplicate listings
indicates productizable workflows · click row for records