为什么数据库未来不再对存储收费
Why Databases Won't Charge for Storage in the Future
Snowflake 财报电话会透露,大型客户正转向 Apache Iceberg 等开放格式,把数据迁出 Snowflake,导致其存储与相关计算收入流失。存储约占 Snowflake 整体收入的 10% 至 11%,总额约 2.8 亿至 3 亿美元。客户推动计算与存储更深层解耦,未来查询引擎将按价格与性能在不同工作负载上竞争。
In short : Explore the future of databases as they shift towards unbundled storage and compute, driven by customer demand for open formats.

The database is being unbundled. Historically, a database like Snowflake sold both data storage & a query engine (& the computing power to execute the query). That’s step 1 above.
But, customers are pushing for a deeper separation of compute & storage. The recent Snowflake earnings call highlighted the trend. Larger customers prefer open formats for interoperability (step 2 & 3).
A lot of big customers want to have open file formats to give them the options…So data interoperability is very much a thing and our AI products can generally act on data that is sitting in cloud storage as well.
We do expect a number of our large customers are going to adopt Iceberg formats and move their data out of Snowflake where we lose that storage revenue and also the compute revenue associated with moving that data into Snowflake.
Instead of locking the data in one database, customers prefer to have it in open formats like Apache Arrow, Apache Parquet, Apache Iceberg.
As data use inside of an enterprise has expanded, so has the diversity of demands on that data.
Rather than copying it each time for a different purpose whether it’s exploratory analytics, business intelligence, or AI workloads, why not centralize the data and then have many different systems access it?
This saves money : Storage is about $280m-300m overall for Snowflake.
As a reminder, about 10% to 11% of our overall revenue is associated with storage.
But it also simplifies architectures.
It also ushers in an epoch where the query engines will compete for different workloads with price & performance. Snowflake may be better for large-scale BI ; Databricks’ Spark for AI data pipelines ; MotherDuck for interactive analytics.
Data warehouse vendors have marketed the separation of storage & compute in the past. But, that message was about scaling the system to handle bigger data within their own product.
Customers demand a deeper separation - a world in which databases don’t charge for storage.
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来源:Tomer Tunguz 博客 · tomtunguz.com