Tigris
S3-compatible global storage for devs and AI agents. Unlimited scale, no egress costs, fork buckets instantly. Built for training, inference, and agent orchestration.
Editor's Verdict
Key Takeaways
- Zero Egress Fees
- Bottomless Storage
- S3 Compatibility
- Copy-on-Write Forks
In-Depth Review: What is Tigris?
Tigris is a modern object storage platform designed for developers and AI agents. It offers bottomless storage with zero egress fees, S3 API compatibility, and global redundancy. Key features include zero-copy forks for experimentation, snapshots for time travel, webhooks for event-driven pipelines, and fine-grained IAM. Tigris also provides an Acceleration Gateway for local caching to boost AI training and inference performance. With zero-downtime migration from existing S3-compatible storage, Tigris eliminates vendor lock-in and simplifies data management at scale.
Core Features
Zero Egress Fees
No charges for data transfer out to the internet or between regions, enabling cost-effective storage and distribution.
Bottomless Storage
Store unlimited amounts of data with no per-account or per-region limits, automatically scaling as needed.
S3 Compatibility
Native S3 API support allows using existing tools like boto3, aws-cli, and rclone without code changes.
Copy-on-Write Forks
Create instant, zero-copy forks of buckets for isolated experimentation, agent sandboxes, or parallel workflows.
Global Geo-Redundancy
Data is automatically redundant across regions with placement options (single, multi, global) for low-latency access worldwide.
Snapshots & Time Travel
Take whole-bucket snapshots for point-in-time recovery, rollback, or auditing with second-level precision.
Acceleration Gateway
A local caching proxy that delivers near-local NVMe throughput for AI training and inference, compatible with any S3 client.
Pricing
Free Tier
- 5 GB Standard storage
- 10,000 Class A requests/month
- 100,000 Class B requests/month
- Zero egress fees
Standard
- Global, single-region, multi-region, or dual-region placement
- No minimum storage retention
- Free data retrieval
- Zero egress fees
Infrequent Access
- Lower storage cost for infrequently accessed data
- 30-day minimum storage retention
- Data retrieval fee: $0.01/GB
- Zero egress fees
Archive
- Lowest storage cost for archival data
- 90-day minimum storage retention
- Free data retrieval (restore to Standard tier)
- Zero egress fees
Archive Instant Retrieval
- Same storage cost as Archive with faster retrieval
- 90-day minimum storage retention
- Data retrieval fee: $0.03/GB
- Zero egress fees
Enterprise
- Custom pricing and service contract
- Tailored for large workloads
- Priority support
Pros and Cons
Pros
- No Egress FeesEliminate data transfer costs, making it ideal for AI/ML workloads with high read volumes across regions.
- Infinite ScalabilityNo storage limits or capacity planning required; scales automatically from gigabytes to petabytes.
- S3 Compatible APIWorks with existing S3 tools and SDKs out of the box, minimizing migration effort.
- Global PerformanceData automatically distributed worldwide for low-latency access, with optional placement controls.
- Purpose-Built AI FeaturesCopy-on-write forks, snapshots, and webhooks enable advanced agent workflows and experimentation.
Cons
- Limited Free TierFree tier only includes 5 GB of storage and limited requests, which may not suffice for larger evaluations.
- Archive Retrieval ComplexityAccessing Archive tier data requires restoration to Standard tier, adding latency and potential costs.
- No Per-Region Pricing ControlPricing is uniform globally, so users with single-region needs may pay for global features they don't use.
- Relatively New ServiceTigris is a newer platform compared to AWS S3 or GCS, which may concern enterprises requiring long-term stability.
- Dependency on CoreWeave InfrastructureThe Acceleration Gateway relies on CoreWeave's network, which might limit flexibility for some hybrid setups.
Use Cases & Recommended Professions
AI Engineer→ View Toolkit
Need scalable, cost-effective storage for training datasets, model checkpoints, and inference pipelines with zero egress fees.
Machine Learning Engineer→ View Toolkit
Require globally distributed object storage that integrates with PyTorch, TensorFlow, and other ML frameworks without code changes.
Data Scientist→ View Toolkit
Benefit from bottomless storage for exploratory data analysis, snapshot-based versioning, and easy collaboration across teams.
DevOps Engineer→ View Toolkit
Use S3-compatible APIs to build CI/CD pipelines, manage artifacts, and automate backup with webhooks and lifecycle rules.
Backend Developer→ View Toolkit
Leverage presigned URLs, custom domains, and fine-grained IAM for secure, scalable user-generated content storage.
AI Agent Developer→ View Toolkit
Utilize copy-on-write forks and workspace management to orchestrate millions of agents with isolated, cheap storage per agent.
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ℹ️ Curation Disclosure: The overview and features of Tigris were synthesized using AI and fact-checked by our curation team to ensure accuracy.
