Statements (78)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Database_Management_System
|
| gptkbp:bfsLayer |
3
|
| gptkbp:bfsParent |
gptkb:football_club
gptkb:AWS gptkb:book gptkb:seal gptkb:server |
| gptkbp:architectural_style |
columnar storage
|
| gptkbp:developed_by |
gptkb:server
|
| gptkbp:has |
security features
user-defined functions data retention policies user management features data access controls Redshift Spectrum feature managed storage query monitoring features |
| https://www.w3.org/2000/01/rdf-schema#label |
Amazon Redshift
|
| gptkbp:integrates_with |
AWS ecosystem
|
| gptkbp:is |
Data Warehouse Service
|
| gptkbp:is_a |
Data warehousing service
|
| gptkbp:is_available_in |
multiple AWS regions
|
| gptkbp:is_compatible_with |
gptkb:seal
ETL tools data lakes |
| gptkbp:is_designed_for |
analytical workloads
|
| gptkbp:is_integrated_with |
gptkb:Amazon_Quick_Sight
gptkb:Amazon_S3 |
| gptkbp:is_known_for |
high performance
scalability fast query performance |
| gptkbp:is_optimized_for |
OLAP workloads
|
| gptkbp:is_part_of |
AWS cloud services
AWS analytics services |
| gptkbp:is_popular_in |
data analysts
|
| gptkbp:is_used_by |
large enterprises
business intelligence tools |
| gptkbp:is_used_for |
reporting
financial analysis big data analytics customer analytics |
| gptkbp:language |
gptkb:SQL
|
| gptkbp:offers |
customizable dashboards
query optimization data compression scalable compute resources cost-effective pricing model data lake integration query result caching |
| gptkbp:provides |
API access
data lineage tracking automatic backups data modeling capabilities data import/export capabilities performance tuning options data security compliance SQL-based querying workload management concurrency scaling |
| gptkbp:release_date |
February 2013
|
| gptkbp:scales |
up to petabytes of data
|
| gptkbp:supports |
data encryption
data governance data integration data migration data sharing data transformation data visualization tools real-time analytics data partitioning data archiving data exploration data warehousing best practices machine learning integration JDBC and ODBC drivers multi-cluster architecture petabyte-scale data warehousing |
| gptkbp:uses |
gptkb:Massively_Parallel_Processing_(MPP)
|