Redis Announces Disk‑Based Tiered Storage to Cut Costs and Boost Appeal
Redis is exploring a disk‑backed tiered storage architecture, allowing infrequently used data to move from memory to flash and back, a move aimed at reducing costs, improving scalability, and expanding its popularity among developers and gaming applications.
Redis recently disclosed that it is working on incorporating disk as part of a tiered storage architecture to lower costs and broaden the system’s appeal.
CEO Rowan Trollope told The Register that the goal is to help customers reduce expenses and simplify their architecture. He noted that while sub‑millisecond distributed systems deliver the performance developers need, other internet‑scale systems such as MongoDB can be more price‑competitive.
To address this, Redis has created a layered memory approach that adds flash support behind its in‑memory engine.
"We are a half‑step between disk and memory. For certain use cases, such as games, companies can use us to provide real‑time leaderboards and other in‑game statistics," Trollope said.
He explained that after the initial hype of a game launch fades, many users become dormant until new content arrives. By using flash, Redis can dynamically tier data: "We can move data that hasn’t been accessed for a long time to flash for a period, and when the user returns we seamlessly move it back to memory, saving costs for the company."
Redis now plans to extend this concept to disk‑based memory, supporting a three‑layer architecture.
According to the Stack Overflow 2023 Developer Survey, Redis ranks as the sixth most popular database and the second most popular NoSQL database among professional developers, with about 23% usage. Sumo Logic’s research also showed Redis as the most popular database on AWS in 2020.
Trollope attributed Redis’s popularity to a lack of direct competition, stating that while other top databases are used alongside Redis, they do not compete head‑to‑head because they are not pure in‑memory databases.
He also revealed that Redis has addressed the lack of SQL support with the RediSQL module, now available on GitHub, and hinted at future features such as natural‑language queries and enhanced vector and feature‑store capabilities.
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