CoreWeave Storage

Name: CoreWeave Storage
Brand: CoreWeave

CoreWeave Storage is a suite of storage services—S3-compatible object storage, POSIX-compliant distributed file storage, and node-local ephemeral storage—designed to deliver low-latency, high-throughput access for GPU-based AI training and inference workloads.

Est 2017|Valuation $30.7B|Raised $49.3B|49 Ref Customers

LinkedIn 147K|Website|Web traffic 495K|FTEs 2,637|HQ New York, NY

MarketsCloud Infrastructure Providers (IaaS/PaaS)

Platform CoversArtifact Management

01Competitive Landscape

| Aspect | CoreWeave Storage | Amazon S3 | VAST Data (Dedicated VAST via CoreWeave) | |--------|---------------|----------------|----------------| | Starting Price | Published per-GB tiered pricing by storage class (hot/warm/cold) and for distributed file; vendor-published tiered pricing available | Varies by region/class; request + monitoring + retrieval fees may apply depending on class | Not publicly standardized; typically quote-based enterprise pricing | | Best For | GPU-near AI pipelines needing high throughput + predictable economics (no egress/request fees) | General-purpose object storage with vast ecosystem, governance, and service integrations | Petabyte-scale single-tenant storage with VAST ecosystem needs, strict isolation/compliance, deep data services | | Key Strength | AI-optimized data path (LOTA caching), unified dataset across regions, simplified fee model | Mature global platform, deep integrations (analytics/eventing/governance), broad compliance programs | High-performance enterprise storage platform features; dedicated hardware isolation | | Key Weakness | Fewer independent reviews; potential platform concentration risk; smaller ecosystem than hyperscalers | Cost complexity at scale (requests, egress, tiering, monitoring); performance may require extra architectural work | Operational complexity and enterprise procurement overhead; cost often opaque | - Narrative analysis - CoreWeave vs AWS S3 - Where CoreWeave may win - AI-specific economics: CoreWeave markets no egress, no request fees, and access-based automated billing (vendor blog and pricing overview). - AI performance design: LOTA caches data on local NVMe on compute nodes; this is described as reducing load times (official product documentation). - Where AWS may win - Ecosystem breadth and tooling maturity; AWS S3 is deeply integrated into AWS analytics, governance, security, and partner ecosystem, and offers multiple storage classes with different retrieval behaviors and fees (AWS product and pricing pages). - Extremely large install base and extensive third-party operational knowledge. - CoreWeave vs dedicated enterprise AI storage (VAST/WEKA/DDN/Pure) - CoreWeave’s dedicated partner storage approach suggests it acknowledges that some workloads need specialized single-tenant storage clusters rather than shared managed storage (product overview and partner pages). - In those cases, buyers should compare: - Operational control (direct VMS access, custom QoS, snapshots, encryption keys). - Cost transparency (CoreWeave publishes list prices for managed storage; enterprise storage vendors are often quote-based). - Support model split (CoreWeave + storage partner responsibilities).

01Competitive Landscape

Aspect	CoreWeave Storage	Amazon S3	VAST Data (Dedicated VAST via CoreWeave)
Starting Price	Published per-GB tiered pricing by storage class (hot/warm/cold) and for distributed file; vendor-published tiered pricing available	Varies by region/class; request + monitoring + retrieval fees may apply depending on class	Not publicly standardized; typically quote-based enterprise pricing
Best For	GPU-near AI pipelines needing high throughput + predictable economics (no egress/request fees)	General-purpose object storage with vast ecosystem, governance, and service integrations	Petabyte-scale single-tenant storage with VAST ecosystem needs, strict isolation/compliance, deep data services
Key Strength	AI-optimized data path (LOTA caching), unified dataset across regions, simplified fee model	Mature global platform, deep integrations (analytics/eventing/governance), broad compliance programs	High-performance enterprise storage platform features; dedicated hardware isolation
Key Weakness	Fewer independent reviews; potential platform concentration risk; smaller ecosystem than hyperscalers	Cost complexity at scale (requests, egress, tiering, monitoring); performance may require extra architectural work	Operational complexity and enterprise procurement overhead; cost often opaque

Narrative analysis
- CoreWeave vs AWS S3
  - Where CoreWeave may win
    - AI-specific economics: CoreWeave markets no egress, no request fees, and access-based automated billing (vendor blog and pricing overview).
    - AI performance design: LOTA caches data on local NVMe on compute nodes; this is described as reducing load times (official product documentation).
  - Where AWS may win
    - Ecosystem breadth and tooling maturity; AWS S3 is deeply integrated into AWS analytics, governance, security, and partner ecosystem, and offers multiple storage classes with different retrieval behaviors and fees (AWS product and pricing pages).
    - Extremely large install base and extensive third-party operational knowledge.
- CoreWeave vs dedicated enterprise AI storage (VAST/WEKA/DDN/Pure)
  - CoreWeave’s dedicated partner storage approach suggests it acknowledges that some workloads need specialized single-tenant storage clusters rather than shared managed storage (product overview and partner pages).
  - In those cases, buyers should compare:
    - Operational control (direct VMS access, custom QoS, snapshots, encryption keys).
    - Cost transparency (CoreWeave publishes list prices for managed storage; enterprise storage vendors are often quote-based).
    - Support model split (CoreWeave + storage partner responsibilities).

Aspect

CoreWeave Storage

Amazon S3

VAST Data (Dedicated VAST via CoreWeave)

Starting Price

Published per-GB tiered pricing by storage class (hot/warm/cold) and for distributed file; vendor-published tiered pricing available

Varies by region/class; request + monitoring + retrieval fees may apply depending on class

Not publicly standardized; typically quote-based enterprise pricing

Best For

GPU-near AI pipelines needing high throughput + predictable economics (no egress/request fees)

General-purpose object storage with vast ecosystem, governance, and service integrations

Petabyte-scale single-tenant storage with VAST ecosystem needs, strict isolation/compliance, deep data services

Key Strength

AI-optimized data path (LOTA caching), unified dataset across regions, simplified fee model

Mature global platform, deep integrations (analytics/eventing/governance), broad compliance programs

High-performance enterprise storage platform features; dedicated hardware isolation

Key Weakness

Fewer independent reviews; potential platform concentration risk; smaller ecosystem than hyperscalers

Cost complexity at scale (requests, egress, tiering, monitoring); performance may require extra architectural work

Operational complexity and enterprise procurement overhead; cost often opaque