Guides and comparisons on cloud storage — from S3, EBS, and EFS to the file systems built on top of them.
How to design a storage strategy for AI systems, from large-scale training datasets to inference and AI agents.
Storage architecture can make or break your AI pipeline. From data ingestion to model training and serving, each phase has different performance and cost requirements. This post breaks down storage tiers, tradeoffs, and practical strategies for optimizing performance without blowing up your cloud bill.
Learn what POSIX compliance means, how it differs from object storage, and why S3 is not POSIX-compliant. Covers the practical impact on application behavior, common migration pitfalls, and which cloud file storage options support true POSIX semantics for workloads that need them.
DeepSeek 3FS is an open-source distributed file system built specifically for large, read-heavy AI workloads. It delivers strong consistency and fast random reads, but comes with slower writes and significant operational complexity, making it a good fit only for teams running AI at serious scale.
Compares JuiceFS and ObjectiveFS, two POSIX-compatible filesystems built on object storage, focusing on their architectural tradeoffs, metadata handling, operational overhead, and consistency models. Helps teams decide whether they prefer an open, operator-managed system or a fully managed filesystem with stronger built-in guarantees and simpler operations.
Compares s3fs and Goofys, two tools for mounting S3 as a local filesystem, and explains how their metadata handling, caching strategies, and API usage impact performance, consistency, and cost. Helps teams understand when filesystem-on-S3 layers are sufficient—and when object-native approaches are a better fit for large-scale data workloads.
Compares Goofys and ObjectiveFS, two ways to mount object storage as a filesystem, and explains how their goals differ. Highlights the tradeoff between lightweight S3 adapters optimized for simplicity and speed versus fully featured POSIX-style filesystems built for consistency, shared access, and multi-machine workloads.
Explains what ObjectiveFS is and how it delivers a fully POSIX-compatible shared filesystem on top of object storage. Covers its architecture, consistency model, performance characteristics, and where it fits best for teams that need scalable, cloud-backed file storage without running a storage cluster.
This guide compares AWS EFS and its cloud storage alternatives—Azure Files, GCP Filestore, Oracle, and Archil—highlighting differences in scalability, performance, and cost to help teams choose the best managed NFS solution for their workloads.
A tactical guide to cutting AWS costs fast—combining 10 proven AWS tools with Archil’s S3-backed, infinite local disk to shrink infrastructure spend, extend runway, and boost efficiency without slowing product velocity.
Learn how to host and scale your WordPress site on AWS using Archil—mount S3 as a local file system for faster performance, simple deployment, and cost-efficient cloud storage without the complexity.
Discover how Amazon S3 Vectors brings vector-native storage to the cloud—and how Archil complements it by delivering local-speed, real-time access to vector data for next-generation AI workflows.
Stop wasting time with aws s3 sync — learn how Archil lets you mount Amazon S3 as a live, POSIX file system for instant access, faster performance, and lower costs.
Optimize Amazon S3 performance with key prefix scaling, S3 Transfer Acceleration, and multi-part uploads to achieve faster throughput, lower latency, and global reliability at any scale.
Learn why tools like s3fs struggle to make S3 behave like a true file system—and how Archil delivers a faster, reliable, POSIX-like alternative built for modern, cloud-native performance.
Set up Jupyter on AWS EC2 with S3 and Archil to build a high-performance, cloud-native analytics environment—mount S3 as a local file system for instant, code-free data access and faster analysis.
Learn the key differences between data lakes, data warehouses, and hybrid solutions—and how to choose the right architecture for analytics, scalability, and real-time insights.
Compare Amazon S3 Express One Zone and caching solutions like Archil—discover when to use high-performance S3 storage vs. dynamic, cost-efficient caching for ultra-low-latency workloads.
Understand AWS EBS volume types, pricing, and cost-optimization strategies—learn how to choose the right storage class, manage performance, and reduce your AWS bill effectively.
Compare AWS EBS vs EFS vs S3—and learn how Archil bridges them by turning S3 into a high-performance, mountable file system that delivers local-disk speed with cloud-scale flexibility.
As companies scale, AWS EBS’s costs and performance limits become clear. Alternatives like Ceph, GlusterFS, and caching layers offer more flexibility and speed. Modern architectures—like Archil’s—combine object storage with caching to deliver faster, more scalable cloud data access.
AWS S3 is known for its massive scale, eleven nines of durability, and global availability. It’s the go-to storage layer for enterprises managing everything from logs and backups t
Lustre is a high-performance distributed file system built for HPC: fast, parallel, and scalable. But as cloud-native, elastic workloads rise, its rigid, server-centric design raises questions about fit in the modern data stack.
S3 Intelligent Tiering auto-optimizes storage costs by moving data across access tiers based on usage—no retrieval fees, no latency impact, and up to 95% savings. Ideal for large, infrequently accessed files. Not worth it for tiny or short-lived objects.
Amazon EFS and S3 serve different needs—EFS offers shared file system access with low latency, while S3 is built for scalable, low-cost object storage. This article compares performance, pricing, and use cases, and introduces Archil as a hybrid solution that blends S3’s affordability with file system speed.
Discover the pros and cons of serverless vs. Kubernetes for modern cloud architecture. Learn when to use each, how to handle persistent storage, and how Archil bridges the gap for scalable, high-performance data access.
Confused about when to use Amazon S3 vs EBS? This in-depth guide compares AWS storage options—performance, pricing, latency, throughput, and real-world use cases—to help you choose the right fit for your application. Learn how cloud-native apps, databases, and AI workloads benefit from the right blend of EBS and S3, plus discover automated caching solutions for maximum speed and savings.
Compare Amazon FSx file systems—Windows, Lustre, ONTAP, OpenZFS—and discover when modern storage alternatives like Archil deliver better performance.