Cloud storage — at a glance
- $0.02–$0.10/GB/month
- Unlimited scaling
- Zero hardware to manage
- Egress fees can surprise you
- AI-ready (S3 + Lambda, etc.)
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San Diego · AI & Cloud Storage
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Storage Guide
AI storage solutions — cloud vs NAS vs on-prem for San Diego businesses
Honest comparison of cloud storage (AWS S3, Google Cloud, Azure), network-attached storage (NAS), and on-premise servers. What actually makes sense for AI workloads, document management, and business data.
NAS (network storage) — at a glance
- $500–$3,000 upfront hardware
- 2TB–50TB typical capacity
- One-time cost, then maintenance
- Local network speed (gigabit+)
- Full control, no recurring fees
The real-world difference
- <500GB? Cloud is cheaper & simpler
- 5TB+? NAS saves money long-term
- AI training models? Cloud GPU access wins
- Video/photo archives? NAS locally is faster
Neither is universally better. Cloud storage wins on convenience and AI integration. NAS wins on cost at scale and local performance. Hybrid setups (NAS + cloud backup) are common for San Diego businesses.
Cost comparison — where the math changes
| Storage need | Cloud (monthly) | NAS (5-year TCO) | Winner |
|---|---|---|---|
| 100GB documents | $2–$5/mo (Google Drive, Dropbox) | $500 NAS ÷ 60 months = $8.30/mo | Cloud (simpler, no hardware) |
| 1TB business files | $20–$50/mo | $800 NAS ÷ 60 = $13.30/mo | NAS (cheaper after 18 months) |
| 5TB photo/video archive | $100–$250/mo | $1,500 NAS ÷ 60 = $25/mo | NAS (90% cheaper long-term) |
| AI model training (100GB datasets) | $5/mo storage + GPU compute as needed | NAS + separate GPU server ($5k+) | Cloud (on-demand GPU access) |
| Backup / disaster recovery | Glacier/Archive: $0.004/GB/mo | Second NAS in different location | Cloud (simpler redundancy) |
| Data egress (downloads) | $0.08–$0.12/GB | Free (local network) | NAS (no egress fees) |
| Setup difficulty | 5 minutes (create bucket/folder) | 2-4 hours (hardware + config) | Cloud (instant) |
Who should use cloud storage
Cloud storage (AWS S3, Google Cloud Storage, Azure Blob, Dropbox Business, Google Workspace) makes sense when you need simplicity, remote access, or AI/ML integrations. No hardware to buy, no maintenance, and built-in redundancy. You're paying for convenience.
Cloud is also the best option for AI workloads — training models, running inference, processing large datasets. Services like AWS SageMaker, Google Vertex AI, and Azure ML integrate directly with cloud storage. Trying to replicate that on-premise hardware costs $50k+ for serious AI work.
- Small teams (<10 people) with <500GB data
- Remote work — team needs access from anywhere
- AI/ML projects requiring GPU compute
- Startups wanting zero upfront hardware cost
- Need automatic backups and disaster recovery
Who should use NAS or on-prem storage
Network-attached storage (Synology, QNAP, TrueNAS) or dedicated file servers make sense when you have predictable, large storage needs and work locally. A $1,500 NAS with 10TB capacity beats cloud costs after 12-24 months if you're storing video, photos, design files, or large databases.
NAS also wins on speed — gigabit or 10GbE network connections blow away internet upload/download speeds. If you're editing 4K video or working with large CAD files in San Diego offices, local NAS access is 10-50x faster than cloud.
- Media companies (video production, photography)
- Businesses with 2TB+ storage needs
- Local office with fast network infrastructure
- Want full control over data location & privacy
- Ready to handle hardware maintenance
Hybrid approach — best of both
Many San Diego businesses use a hybrid setup: NAS for active working files (fast local access), cloud for backup and remote access. Synology and QNAP NAS devices have built-in cloud sync to Dropbox, Google Drive, or S3.
Example: A design agency stores current project files on a local 10TB NAS for fast editing. Every night, completed projects auto-sync to Google Cloud Storage (Coldline tier at $0.004/GB/mo). Team gets local speed + cloud disaster recovery.
- Best cost balance (local performance, cloud backup)
- Resilience (if NAS dies, cloud backup recovers)
- Flexibility (remote workers access cloud copy)
- Downside: More complexity to manage
AI-specific storage considerations
If you're training AI models or running inference at scale, cloud storage with integrated GPU compute is almost always the right choice. AWS S3 + SageMaker, Google Cloud Storage + Vertex AI, or Azure Blob + ML Studio give you seamless data → training pipeline.
On-premise AI work requires expensive GPU servers ($10k–$100k), power/cooling infrastructure, and specialized knowledge. Only makes sense at very large scale (enterprise research labs) or when data cannot leave premises (medical, defense).
For San Diego startups doing AI/ML work: start with cloud. You can always migrate to on-prem later if cost justifies it.
Real San Diego business scenarios
How the storage decision plays out for different local business types.
🎬 Video production company — 20TB archive
Finished projects, raw footage, client deliverables. Fast local access needed for editing.
→ NAS primary ($2k Synology 20TB) + Google Cloud Coldline backup. Saves $1,800/year vs cloud-only.
🤖 AI startup — training sentiment models
100GB training datasets, need GPU compute for model training, remote team.
→ Cloud only (AWS S3 + SageMaker). On-demand GPU access, no upfront hardware cost.
🏢 Accounting firm — 800GB client files
Tax docs, scanned records, QuickBooks backups. 5-person office, occasional remote access.
→ NAS locally ($900 Synology 4TB) + nightly Backblaze B2 backup ($4/mo). Total control, low cost.
📱 App developer — 200GB code + assets
Git repos, app builds, design assets. Fully remote 3-person team.
→ Cloud only (GitHub + Google Workspace). Remote access is priority, volume is small.
Bottom line
If you have <500GB and work remotely: use cloud storage (Google Workspace, Dropbox Business). Simple, instant, no hardware.
If you have 2TB+ and work from a San Diego office: buy a NAS. Cheaper after 18 months, faster local access, full control.
If you're doing AI/ML work: use cloud. GPU compute + storage integration is unbeatable.
Hybrid NAS + cloud backup is the sweet spot for many businesses.
Common questions
What's the minimum hardware for a reliable NAS?+
Synology DS220+ (~$300) or QNAP TS-251D (~$350) with 2x 4TB drives (~$200) = ~$500 total for 4TB usable (RAID 1 mirroring). For business use, spend $900-$1,500 for 4-bay units with redundancy and better performance.
How do cloud egress fees work?+
Uploading data to AWS/Google/Azure is free. Storage is cheap ($0.02–$0.10/GB/mo). But downloading (egress) costs $0.08–$0.12/GB. If you frequently download terabytes of data, NAS is cheaper. If data mostly stays in cloud (AI training, archives), egress is minimal.
Can I use NAS for remote access?+
Yes. Synology QuickConnect and QNAP myQNAPcloud let you access NAS files remotely through VPN or web portal. Speed is limited by your office internet upload (typically 10-35 Mbps in San Diego). Cloud storage is faster for remote workers.
What if my NAS dies?+
Use RAID for drive redundancy (one drive can fail, data stays safe). Also run nightly cloud backups to Backblaze B2 ($0.005/GB/mo) or Wasabi ($0.006/GB/mo) for disaster recovery. Hybrid setup = local speed + cloud safety net.
Which cloud provider is cheapest?+
For raw object storage: Backblaze B2 ($0.005/GB/mo) and Wasabi ($0.006/GB/mo) beat AWS S3 ($0.023/GB/mo). But AWS/Google/Azure include AI/ML integrations, better tooling, and global CDN. For simple backups: Backblaze. For AI work: AWS/Google/Azure.
What about Dropbox or Google Drive for business?+
Dropbox Business ($12.50/user/mo for unlimited) and Google Workspace ($12/user/mo for 2TB/user) are simplified cloud storage with sync/collaboration. Easier than raw S3/Azure, more expensive at scale. Great for <10-person teams. For AI/ML or large archives, use raw cloud storage or NAS.
Not sure which storage approach fits your needs?
Text PJ directly. Describe your data size, team setup, and use case.
(773-544-1231) · San Diego
(773-544-1231) · San Diego