Massively Parallel Processing (MPP)
GPTKB entity
Statements (56)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:microprocessor
|
| gptkbp:canBe |
thousands of processors
|
| gptkbp:characterizedBy |
multiple processors
|
| gptkbp:designedFor |
large-scale data processing
|
| gptkbp:enables |
high performance computing
|
| gptkbp:facilitates |
real-time data processing
|
| https://www.w3.org/2000/01/rdf-schema#label |
Massively Parallel Processing (MPP)
|
| gptkbp:isAccessibleBy |
Symmetric_Multiprocessing_(SMP)
|
| gptkbp:isAssociatedWith |
gptkb:Hadoop_ecosystem
|
| gptkbp:isAttendedBy |
financial services
large enterprises research institutions telecommunications companies healthcare_organizations |
| gptkbp:isBeneficialFor |
data analysis
complex queries report generation high-volume transactions |
| gptkbp:isChallengedBy |
network latency
data consistency issues data skew |
| gptkbp:isEnhancedBy |
data visualization tools
machine learning algorithms AI technologies advanced analytics tools |
| gptkbp:isEvaluatedBy |
performance metrics
scalability ease of use cost-effectiveness |
| gptkbp:isFundedBy |
AI-driven optimizations
edge computing developments quantum_computing_advancements |
| gptkbp:isLocatedIn |
gptkb:Microsoft_Azure_Synapse_Analytics
gptkb:Google_BigQuery Amazon Redshift database systems Snowflake Teradata |
| gptkbp:isOptimizedFor |
read-heavy workloads
|
| gptkbp:isRelatedTo |
distributed computing
|
| gptkbp:isSupportedBy |
data lakes
in-memory databases parallel file systems columnar storage formats |
| gptkbp:isUsedFor |
business intelligence
data integration data mining machine learning tasks ETL_processes |
| gptkbp:isUsedIn |
big data analytics
cloud computing environments |
| gptkbp:requires |
scalable storage solutions
efficient data distribution high-speed interconnects |
| gptkbp:supports |
parallel execution of tasks
|
| gptkbp:usedIn |
data warehousing
|