![]() By allowing you to tier data to object storage without leaving Timescale Cloud, we avoid the need to remove data from your database in an attempt to lower costs or to avoid hard limits related to disk capacity. ![]() Products like Amazon RDS for PostgreSQL and Amazon Aurora work great for small deployments, but once the project grows, databases in RDS and Aurora start getting prohibitively expensive. This feature is a step forward to solving a pressing problem we keep hearing from developers: it is simply too expensive and difficult to scale PostgreSQL databases in AWS. We’ll disclose our final pricing for tiered data in the following weeks, but don’t worry-you won’t lose what you saved: the object storage will be priced roughly 10x cheaper than our regular storage. During the Early Access period, this feature will be entirely free for all Timescale Cloud customers, meaning that you won’t be charged for the volume of data tiered to the object store during that time. We're also rolling out a special offer to celebrate this awesome achievement (we can’t wait for you to try this!). There are no limitations to the data volume you can tier to object storage, and you’ll be charged only for what you store-no extra charge per query or data read, and no hidden costs. Your Timescale Cloud hypertables now seamlessly stretch across our regular and object storage, boosting performance for your most recent data and lowering storage costs for older data. ![]() This storage layer is an integral part of your database. Yet the data still remains fully queryable from within your database, and this tiering is transparent to your application. By running a simple command on your hypertable ( add_tiering_policy), you can automatically tier older data to a low-cost, infinite storage layer built on Amazon S3. ![]() Today, we’re happy to announce that data tiering is available in Early Access for all Timescale Cloud customers. Last November, we announced that we were building an integrated object storage layer to scale PostgreSQL further in a cost-effective way. ![]()
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