Microsoft Azure Data Lake Storage
GPTKB entity
Statements (59)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:cloud_storage
|
| gptkbp:developed_by |
gptkb:Microsoft
|
| https://www.w3.org/2000/01/rdf-schema#label |
Microsoft Azure Data Lake Storage
|
| gptkbp:integrates_with |
gptkb:Azure_Data_Factory
gptkb:Azure_Synapse_Analytics gptkb:Azure_Databricks |
| gptkbp:is_accessible_by |
gptkb:Azure_CLI
gptkb:Azure_Portal SDKs |
| gptkbp:is_available_in |
Multiple regions
Hybrid cloud Private cloud Public cloud |
| gptkbp:is_compatible_with |
gptkb:Apache_Spark
gptkb:Hadoop |
| gptkbp:is_integrated_with |
gptkb:Azure_Machine_Learning
gptkb:Azure_Stream_Analytics gptkb:Power_BI gptkb:Azure_Functions gptkb:Azure_Logic_Apps |
| gptkbp:is_optimized_for |
Data lakes
Analytics workloads |
| gptkbp:is_part_of |
gptkb:Microsoft_Azure
Microsoft Azure ecosystem Big data ecosystem |
| gptkbp:is_scalable |
Petabytes of data
|
| gptkbp:is_used_by |
Enterprises
Government agencies Startups Data scientists Data engineers |
| gptkbp:is_used_for |
Data analysis
Data processing Data storage Data lake architecture |
| gptkbp:offers |
Data lifecycle management
Security features Integration with machine learning services Cost-effective storage options |
| gptkbp:provides |
High availability
Data versioning Data sharing capabilities Monitoring and logging features Scalable storage for big data analytics Data ingestion capabilities |
| gptkbp:supports |
Data encryption
Stream processing Batch processing Data governance Data integration Data analytics tools Data transformation Hierarchical namespace Access control lists (ACLs) Multiple data formats Multi-cloud strategies |
| gptkbp:uses |
REST APIs
|
| gptkbp:bfsParent |
gptkb:Microsoft
|
| gptkbp:bfsLayer |
4
|