I’ve been spending some time developing with Shelby, the hot storage network being built by Aptos Labs and Jump Crypto, and wanted to share a few grounded observations from the builder side.
From the documentation and early materials, Shelby is positioned as a decentralized hot storage layer designed for real-time and data-intensive Web3 workloads. The key distinction, compared to existing storage solutions, is that Shelby is explicitly not meant for long-term archival use cases, but for low-latency, frequently accessed data.
While working through the design constraints, a few things stand out clearly:
1. Shelby is optimized for sub-second data access
Shelby’s core goal is to support applications that need fast reads and frequent access. This makes it relevant for use cases where traditional decentralized storage solutions are too slow.
2. Designed for real-time Web3 applications
Shelby is being built with workloads like real-time applications, content-heavy systems, and data-driven services in mind. The focus is on enabling decentralized applications to handle scale and performance requirements that are difficult to meet with on-chain storage alone.
3. Still early, but directionally clear
From a builder perspective, Shelby is clearly early-stage, but its intended role in the Aptos ecosystem is well-defined: enabling performant, decentralized data access without overloading the base layer.
At this stage, my focus has mainly been on understanding:
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how Shelby fits into an Aptos-based architecture,
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which types of data are appropriate for Shelby versus on-chain storage,
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and how this changes the way dApps can be structured at a high level.
I’ll share more concrete learnings once there’s hands-on experience to report, but wanted to document these initial, spec-driven observations for others exploring Shelby.
If others here are also evaluating Shelby, curious how you’re thinking about data separation and use cases.