Data Management Glossary nnn
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A
- Active Storage
- Adaptive Data Management
- AI Agents
- AI and Corporate Data
- AI Compute
- AI Data Extraction
- AI Data Governance
- AI Data Ingestion
- AI Data Leakage
- AI Data Management
- AI Data Pipelines
- AI Data Preparation
- AI Data Workflows
- AI Inferencing
- AI Infrastructure
- Air Gap
- Alternate Data Streams (ADS)
- Amazon (AWS) S3 Intelligent Tiering
- Amazon FSx
- Amazon Glacier (AWS Glacier)
- Amazon S3 (AWS S3)
- Amazon S3 Glacier Instant Retrieval
- Amazon Tiering
- Analytics-driven Data Management
- Application Programming Interface (API)
- Archival Storage
- Archiving
- Artificial Intelligence (AI)
- AWS DataSync
- AWS Lambda
- AWS Snowball
- AWS Storage
- Azure Data Box
- Azure NetApp Files
- Azure Storage
- Azure Tiering
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C
- Capacity Planning
- Carbon footprint
- Carbon Usage Effectiveness
- Chain of Custody
- Chargeback
- Checksum
- Cloud Archiving
- Cloud Cost Optimization
- Cloud Costs
- Cloud Data Analytics
- Cloud Data Growth Analytics
- Cloud Data Management
- Cloud Data Migration
- Cloud Data Storage
- Cloud File Storage
- Cloud Migration
- Cloud NAS
- Cloud Object Storage
- Cloud Storage Gateway
- Cloud Tiering
- CloudPools
- Cold Data
- Common Internet File System (CIFS)
- Compression
-
D
- Dark Data
- Data Analytics
- Data Archiving
- Data Backup
- Data Center Consolidation
- Data Center Emissions
- Data Classification
- Data Curation
- Data Governance
- Data Hoarding
- Data Indexing
- Data Lake
- Data Lakehouse
- Data Lifecycle Management
- Data Lineage
- Data Literacy
- Data Management
- Data Management for AI
- Data Management Policy
- Data Migration
- Data Migration Chain of Custody
- Data Migration Plan
- Data Migration Software
- Data Migration Warm Cutover
- Data Mobilization
- Data Orchestration
- Data Protection
- Data Retention
- Data Retrieval
- Data Services
- Data Silos
- Data Sprawl
- Data Storage
- Data Storage Costs
- Data Storage Management Services (DSMS)
- Data Storage Optimization
- Data Storage Tags
- Data Tagging
- Data Tiering
- Data Transfer
- Data Virtualization
- Deduplication
- Deep Analytics
- Dell PowerScale
- Dell PowerScale SmartPools
- Department Showback
- Digital Business
- Digital Pathology Data Management
- Direct Data Access
- Director (Komprise Director)
- Disaster Recovery
- Dynamic Data Analytics
- Dynamic Links
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E
-
F
-
G
-
H
-
I
-
K
-
M
-
N
-
O
-
P
-
R
-
S
- S3
- S3 Data Migration
- S3 Intelligent Tiering
- Scale-Out Grid
- Scale-Out Storage
- Secondary Storage
- Sensitive Data Detection
- Shadow AI
- Shadow IT
- Sharding
- Shared-Nothing Architecture
- Showback
- Smart Data Workflows
- SmartPools
- SMB Data Migration
- SMB protocol (Server Message Block)
- Solid State Drives (SSDs)
- Storage Area Network (SAN)
- Storage Array
- Storage as a Service
- Storage as a Service (STaaS)
- Storage Assessment
- Storage Costs
- Storage Efficiency
- Storage Insights
- Storage Metrics
- Storage Pool
- Storage Reclamation
- Storage Refresh
- Storage Tiering
- Stubs
- Sustainable Data Management
- Symbolic Link
- System Metadata
-
U
- Unstructured Data
- Unstructured Data AI
- Unstructured Data Analytics
- Unstructured Data Classification
- Unstructured Data Governance
- Unstructured Data Management
- Unstructured Data Migration
- Unstructured Data Preparation
- Unstructured Data Storage
- Unstructured Data Tiering
- Unstructured Data Workflows
- Unstructured Metadata
Stubs
What are Stubs?
Stubs are placeholders of the original data after it has been migrated to the secondary storage. Stubs replace the archived files in the location selected by the user during the archive. Because stubs are proprietary and static, if the stub file is corrupted or deleted, the moved data gets orphaned. Komprise does not use stubs, which eliminates this risk of disruption to users, applications, or data protection workflows.
Challenges with Stubs
Stubs are brittle. When stubbed data is moved from its storage (file, object, cloud, or tape) to another location, the stubs can break. The storage management system no longer knows where the data has been moved to and it becomes orphaned, preventing data access. Most storage management solutions on the market use client-server architecture and do not scale to support data at massive scale.
Proprietary interface like stubs can be used to make tiered data appear to reside on primary storage, but the transparency ends there. To access data, the storage management system intercepts access requests, retrieves the data from where it resides, and then rehydrates it back to primary storage. This process adds latency and increases the risk of data loss and corruption.
Standards-Based Transparent Data Tiering
A true transparent data tiering solution creates no disruption, and that’s only achievable with a standards-based approach. Komprise Intelligent Data Management is the only standards-based transparent data tiering solution that uses Transparent Move Technology™ (TMT), which uses Dynamic Links that are based on industry-standard symbolic links instead of proprietary stubs.
Learn more about the differences between stubs, symbolic links and Dynamic Links from Komprise.
Read the Komprise Architecture Overview white paper to learn more.
Related Terms
Getting Started with Komprise:
- Learn about Intelligent Data Management
- Schedule a demonstration with our team
- Read the latest State of Unstructured Data Management Report
