cloud_regions_metadata
17 rows where wt-region-id = "IND"
This data as json, CSV (advanced)
Suggested facets: year, cloud-provider, cloud-region, cfe-region, em-zone-id, location, geolocation, provider-cfe-hourly, provider-cfe-annual, power-usage-effectiveness, water-usage-effectiveness, provider-carbon-intensity-market-annual, provider-carbon-intensity-average-consumption-hourly, grid-carbon-intensity-average-consumption-annual, grid-carbon-intensity-marginal-consumption-annual, grid-carbon-intensity-average-production-annual, grid-carbon-intensity
| Link | rowid ▼ | year | cloud-provider | cloud-region | cfe-region | em-zone-id | wt-region-id | location | geolocation | provider-cfe-hourly | provider-cfe-annual | power-usage-effectiveness | water-usage-effectiveness | provider-carbon-intensity-market-annual | provider-carbon-intensity-average-consumption-hourly | grid-carbon-intensity-average-consumption-annual | grid-carbon-intensity-marginal-consumption-annual | grid-carbon-intensity-average-production-annual | grid-carbon-intensity | total-ICT-energy-consumption-annual | total-water-input | renewable-energy-consumption | renewable-energy-consumption-goe | renewable-energy-consumption-ppa | renewable-energy-consumption-onsite |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 7 | 7 | 2023 | Google Cloud | asia-south1 | Maharashtra | IN-WE | IND | Mumbai | 19.0761,72.8775 | 0.14 | 0.0 | 648.0 | 746.98 | 762.24 | |||||||||||
| 8 | 8 | 2023 | Google Cloud | asia-south2 | Uttar Pradesh | IN-NO | IND | Delhi | 28.6092,76.9798 | 0.29 | 0.0 | 529.0 | 563.1 | 562.0 | |||||||||||
| 46 | 46 | 2023 | Amazon Web Services | ap-south-2 | Hyderabad | IN-SO | IND | Asia Pacific (Hyderabad) | 17.385,78.4867 | 1.5 | 0.18 | 0.0 | 551.31 | 549.72 | |||||||||||
| 49 | 49 | 2023 | Amazon Web Services | ap-south-1 | Maharashtra | IN-WE | IND | Asia Pacific (Mumbai) | 19.0761,72.8775 | 1.44 | 0.18 | 0.0 | 746.98 | 762.24 | |||||||||||
| 88 | 88 | 2023 | Microsoft Azure | indiasouthcentral | India | IN-SO | IND | India South Central | 17.385,78.4867 | 551.31 | 549.72 | ||||||||||||||
| 105 | 105 | 2022 | Google Cloud | asia-south1 | Maharashtra | IN-WE | IND | Mumbai | 19.0761,72.8775 | 0.24 | 0.0 | 555.0 | 747.67 | 679.4097431 | 760.68 | 679.0 | |||||||||
| 106 | 106 | 2022 | Google Cloud | asia-south2 | Uttar Pradesh | IN-NO | IND | Delhi | 28.6092,76.9798 | 0.23 | 0.0 | 632.0 | 552.52 | 679.4097431 | 552.19 | 679.0 | |||||||||
| 142 | 142 | 2022 | Amazon Web Services | ap-south-2 | Hyderabad | IN-SO | IND | Asia Pacific (Hyderabad) | 17.385,78.4867 | 1.0 | 0.19 | 0.0 | 504.69 | 679.4097431 | 501.99 | 679.0 | |||||||||
| 145 | 145 | 2022 | Amazon Web Services | ap-south-1 | Maharashtra | IN-WE | IND | Asia Pacific (Mumbai) | 19.0761,72.8775 | 1.0 | 1.43 | 0.19 | 0.0 | 747.67 | 679.4097431 | 760.68 | 679.0 | ||||||||
| 184 | 184 | 2022 | Microsoft Azure | indiasouthcentral | India | IN-SO | IND | India South Central | 17.385,78.4867 | 0.46 | 1.43 | 0.0 | 504.69 | 679.4097431 | 501.99 | 679.0 | |||||||||
| 201 | 201 | 2021 | Google Cloud | asia-south1 | Maharashtra | IN-WE | IND | Mumbai | 0.1 | 0.0 | 670.0 | 744.77 | 761.97 | ||||||||||||
| 202 | 202 | 2021 | Google Cloud | asia-south2 | Uttar Pradesh | IN-NO | IND | Delhi | 0.08 | 0.0 | 671.0 | 525.89 | 525.92 | ||||||||||||
| 236 | 236 | 2021 | Amazon Web Services | ap-south-2 | Hyderabad | IN-SO | IND | Asia Pacific (Hyderabad) | 499.35 | 498.15 | |||||||||||||||
| 239 | 239 | 2021 | Amazon Web Services | ap-south-1 | Maharashtra | IN-WE | IND | Asia Pacific (Mumbai) | 744.77 | 761.97 | |||||||||||||||
| 265 | 265 | 2020 | Google Cloud | asia-south1 | Maharashtra | IN-WE | IND | Mumbai | 0.12 | 0.0 | 721.0 | 686.92 | 698.28 | ||||||||||||
| 266 | 266 | 2020 | Google Cloud | asia-south2 | Uttar Pradesh | IN-NO | IND | Delhi | 0.0 | 0.0 | 657.0 | 502.51 | 507.31 | ||||||||||||
| 292 | 292 | 2019 | Google Cloud | asia-south1 | Maharashtra | IN-WE | IND | Mumbai | 0.0 | 0.0 | 752.0 | 706.62 | 707.47 |
Advanced export
JSON shape: default, array, newline-delimited
CREATE TABLE "cloud_regions_metadata" ( [year] INTEGER, [cloud-provider] TEXT, [cloud-region] TEXT, [cfe-region] TEXT, [em-zone-id] TEXT, [wt-region-id] TEXT, [location] TEXT, [geolocation] TEXT, [provider-cfe-hourly] FLOAT, [provider-cfe-annual] FLOAT, [power-usage-effectiveness] FLOAT, [water-usage-effectiveness] FLOAT, [provider-carbon-intensity-market-annual] FLOAT, [provider-carbon-intensity-average-consumption-hourly] FLOAT, [grid-carbon-intensity-average-consumption-annual] FLOAT, [grid-carbon-intensity-marginal-consumption-annual] FLOAT, [grid-carbon-intensity-average-production-annual] FLOAT, [grid-carbon-intensity] FLOAT, [total-ICT-energy-consumption-annual] INTEGER, [total-water-input] INTEGER, [renewable-energy-consumption] INTEGER, [renewable-energy-consumption-goe] INTEGER, [renewable-energy-consumption-ppa] INTEGER, [renewable-energy-consumption-onsite] INTEGER );