Table of Contents
2. SCALITY Software and Services
3.1. What type of information we collect
3.2. What information we do not collect
Specific Provisions — United States
1.3. Purpose of use and legal basis
1.6. California residents' privacy rights
1.7. Change to the Privacy Policy (Specific Provisions)
Specific Provisions — United Kingdom
3.4. How is your Personal Data collected?
3.5. How we use your personal data
3.6. Purpose of use and legal basis
3.9. Withdrawal of your consent
Home/Glossary
Scality glossary
Clear definitions for enterprise storage, AI infrastructure and data protection.
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- AI & data infrastructure
- Data protection & recovery
- Cloud & architecture
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A
- Active-active disaster recoveryMultiple sites serve production workloads, allowing surviving sites to continue when one fails.
- AI data architectureThe design for how data is collected, stored, processed and delivered for AI workloads.
- AI data infrastructureThe storage, compute and networking that support AI data throughout its lifecycle.
- AI data managementThe practices used to organize, govern, protect and retain data for AI.
- AI data pipelineThe stages that move data from ingestion and preparation to training and inference.
- AI data platformAn environment for storing, governing and delivering the data AI applications use.
- AI data readinessWhether data and infrastructure are accessible, governed and scalable enough for an AI use case.
- AI storageStorage built for the capacity, throughput and access patterns of AI and machine learning.
B
- Backup compressionReduces the size of backup data to save storage space and bandwidth.
- Block storageCapacity presented as numbered fixed-size blocks, consumed by file systems, databases and virtual machines.
- Breach containmentActions and controls that limit the impact and spread of a security incident.
C
D
- Data durabilityThe probability stored data survives a period, set by redundancy, failure domains and rebuild time.
- Data fabricAn architecture that connects data across systems, clouds and locations for consistent access.
- Data gravityThe tendency for applications and compute to move closer to large concentrations of data.
- Data lakeA central repository that stores data in its original format for analytics and AI.
- Data localityKeeping data close to the compute and users that need it to reduce network movement.
- Data mobilityThe ability to move data between systems, sites and clouds without losing access or integrity.
- Data replicationCreating and maintaining copies of data across systems or sites so it stays available.
- Distributed file systemFiles spread across many servers but presented as a single file system.
- Distributed storageStorage that spreads data across many nodes so capacity and resilience grow with scale.
E
M
O
S
- S3 compatible storageAny storage system that can be accessed through the Amazon S3 API without being Amazon S3.
- Sequential vs. random I/OReading data in stored order versus jumping between scattered locations.
- SOC reportAn independent auditor's report on the controls a service provider has in place.
- Storage latencyThe time one storage operation takes, often dominated by queueing and network round trips.
- Storage lifecycle managementPolicy-driven placement, protection, retention and deletion of data over its lifecycle.
- Storage managementThe ongoing work of running a storage system: provisioning, protection, monitoring and access.
- Storage performance tuningOptimising cache, controller, network and application layers for throughput and latency.