Cloud platform for a media company storing and processing large video files

A strong default is AWS: use Amazon S3 for durable storage and AWS Elemental MediaConvert for file-based video processing and transcoding. AWS also provides a reference video-on-demand workflow that connects S3 uploads to MediaConvert. (aws.amazon.com)

A typical setup:

• S3: originals, working assets, and finished versions, with lifecycle rules to move infrequently accessed footage into lower-cost archive storage.
• MediaConvert: create delivery formats, renditions, and streaming packages.
• Shared editing storage: add Amazon FSx if editors or render jobs need high-performance shared file access; object storage alone isn’t always a substitute for an editing filesystem. (aws.amazon.com)

Google Cloud is also a good fit if your team already uses it: Cloud Storage pairs with the Transcoder API for video jobs. (docs.cloud.google.com)

The main decision points are editing vs. archive, monthly ingest volume, how often footage is retrieved, and where editors are located—those affect both storage design and transfer costs. If you share those details, I can suggest a more specific architecture.

Short answer: For a media company handling large video files, AWS is the strongest default because it has the most mature first-party media stack. Google Cloud is worth considering if AI-driven video analysis is central to your work. Azure is viable for storage and delivery, but you would need third-party tools for encoding and streaming.

Why AWS is the usual pick

• Its managed media suite covers the main pipeline: transcoding, live streaming, packaging, media-optimized storage, and a CDN. A 2026 comparison lists Elemental MediaConvert (video transcoding), MediaLive (live video streaming), MediaPackage (video delivery), MediaStore (media-optimized storage), CloudFront (CDN with 410+ POPs).
• Scale is proven in practice. One analysis notes that Netflix runs its control plane, encoding pipeline and data platform on AWS, while its video delivery uses its own CDN, Open Connect, rather than AWS.
• Storage costs can be controlled with tiering. Large archives can move between storage classes as they age, which matters for big video libraries.

Google Cloud

• Its strength is AI and analytics. One comparison rates its video AI as Very Strong (Vision AI) against AWS's Rekognition-based offering. Choose GCP if automated tagging, search, or moderation across your library is a priority.
• Its network is a selling point. One source claims measurably lower inter-region latency and more consistent network performance than AWS and Azure, though that comes from a vendor-style blog, so verify it with your own tests.

Azure

• Be aware that Azure Media Services was retired on 30 June 2024, taking with it Microsoft's first-party encoding, packaging, live streaming and built-in DRM licence delivery. Any guide recommending Azure Media Services for new work is out of date.
• Azure still makes sense for storage and delivery, and especially if you already license heavily through Microsoft. Encoding and streaming would come from partners such as Bitmovin or Harmonic.

Practical advice before you commit

• Model egress costs early. Video delivery and cross-region transfers often dominate the bill more than storage does. Commitment discounts (1–3 years) are available, but they should be sized from real usage.
• Pilot your actual workload. Transcode a representative set of your files on two providers and compare time, quality, and cost.
• Check pricing on each provider's official pricing pages. Published comparison figures vary widely between sources and go stale quickly.
• Plan for multi-region storage and a second cloud or a backup copy if the content is business-critical.

Suggested next step: Tell me your monthly storage volume, daily encoding hours, expected viewer geography, and whether you do live streaming. I can then narrow this to a specific architecture and rough cost model.

For a media company handling large video files, a "one-size-fits-all" cloud drive (like basic Google Drive or Dropbox) is often insufficient because these services rely on "sync-and-wait" workflows that are impractical for 4K/8K footage.

The industry standard is to adopt a hybrid approach that separates active production (editing) from long-term archival.

1. The Recommended Workflow

• Active Editing (Hot Storage/Streaming): Do not use traditional file-syncing services. Instead, use a cloud-native streaming file system like LucidLink.
  • Why: It allows editors to stream only the bits of the video file needed for the current frame, acting like a local hard drive without requiring a full download. It is compatible with Adobe Premiere Pro, DaVinci Resolve, and Final Cut Pro.
• Long-Term Archival (Cold Storage): Use cost-effective object storage for completed projects.
  • Options: Backblaze B2 or Wasabi are highly recommended for media companies because they offer predictable, low-cost pricing with no (or very low) egress fees, unlike the major hyperscalers (AWS/Azure/GCP) which can become prohibitively expensive when retrieving large archives.

2. Cloud Platform Options

If you prefer a large, all-in-one ecosystem or have specific compute/AI needs, the "Big Three" offer powerful tools, though they require more technical management:

| AWS | Enterprise/Scale | Massive ecosystem; deep integration with media services (AWS Elemental) for large-scale transcoding. |
| Google Cloud | AI & Analytics | Superior machine learning/AI tools (Vertex AI) for auto-tagging footage and data-heavy analytics. |
| Azure | Integration | Best if your team is already deep in the Microsoft ecosystem; strong enterprise compliance features. |

3. Essential Media-Specific Tools

For processing (transcoding) and collaboration, integrate these specialized platforms into your cloud storage:

• Transcoding: If you need automated processing (turning raw files into H.264/H.265/HLS streams), services like Encoding.com or purpose-built media cloud providers like Dollu and Akamai provide highly optimized, scalable pipelines.
• Review & Approval: Tools like Frame.io (integrates with Adobe) allow clients and teams to provide frame-accurate feedback directly on the video without needing to download files.
• Media Asset Management (MAM): As your library grows, you will need a MAM (e.g., iconik, CatDV) to index and search your files, as standard folder structures become difficult to manage at scale.

Summary Strategy for You

1. Stop syncing entire projects to local computers.
2. Mount your cloud storage using LucidLink for active, real-time collaboration.
3. Offload finished projects to Wasabi or Backblaze B2 to keep costs low while ensuring the data is secure and retrievable.
4. Use a dedicated review tool (like Frame.io) for client feedback to prevent "version control" chaos.

For a media company handling large video files, AWS is a strong end-to-end option:

• Store originals and outputs in Amazon S3. Use storage tiers and lifecycle policies to move infrequently accessed footage into lower-cost archive storage.
• Process video with AWS Elemental MediaConvert to create delivery formats and renditions.
• Automate ingest and analysis with Media2Cloud on AWS, which can orchestrate uploads, generate proxy videos and thumbnails, extract metadata, and support search and analysis workflows. ⁴¹²
• Plan for transfer and processing costs as well as storage: large uploads, transcoding, archive retrieval, and delivery can all affect the bill. AWS’s published Media2Cloud estimate illustrates how strongly processing and analysis costs can vary with workload and settings. ⁸

Google Cloud is also a viable alternative: Cloud Storage holds the input and output files, and the Transcoder API handles transcoding and packaging for formats such as MP4, HLS, and MPEG-DASH. ¹²

Practical recommendation: shortlist AWS and Google Cloud, then compare them using your expected footage volume, upload locations, retention period, processing hours, delivery traffic, and any existing cloud commitments. Those details will determine the best fit and actual cost.