AWS Timestream cost: writes, tiered storage, and queries scanned

Quick answer

Timestream bills writes per million, storage in two tiers (a fast memory store per GB-hour and a cheaper magnetic store per GB-month), and queries per GB scanned. The levers are tuning how long data stays in the expensive memory tier before moving to magnetic, and writing queries that scan less data. Retention configuration is the main control.

Amazon Timestream is a purpose-built time-series database, and its pricing reflects the time-series lifecycle: recent data lives in a fast, expensive tier, older data moves to a cheap tier, and you pay to write and to query. Configuring that lifecycle well is where the cost is decided.

Writes, storage tiers, and queries

Dimension	Bills for
Writes	Per million writes
Memory store	Per GB-hour (fast, recent data)
Magnetic store	Per GB-month (cheap, older data)
Queries	Per GB scanned

Writes are billed per million records. Storage is split: the memory store holds recent data for fast queries at a per-GB-hour rate, and the magnetic store holds older data cheaply at a per-GB-month rate. Queries are billed per gigabyte scanned, like Athena.

Tune the memory retention window

The memory store is far more expensive per gigabyte than the magnetic store, so how long you keep data in memory before it moves to magnetic is the biggest lever. Keep the memory retention window only as long as your fast, recent-data queries need; let everything older move to the cheap magnetic tier. Over-long memory retention is the common overspend.

Scan less on queries

Because queries bill per gigabyte scanned, the same discipline as Athena applies: filter on time ranges and dimensions so queries read only the data they need, and avoid scanning long histories when a recent window would do. Well-scoped queries cut the query line directly.

Controlling Timestream cost

Set the memory-store retention to the minimum your recent-data queries require, let older data age into the magnetic tier, write efficiently (batch writes reduce per-write overhead), and scope queries tightly to reduce data scanned. The two storage tiers and the query-scan model mean retention tuning and query scoping are the whole optimization.

FAQ

How is AWS Timestream priced?

By writes (per million records), storage in two tiers (a fast memory store per GB-hour for recent data and a cheaper magnetic store per GB-month for older data), and queries per gigabyte scanned. Tuning the memory retention window and scanning less on queries are the main levers.

How do I reduce Timestream cost?

Set the memory-store retention to the minimum your recent-data queries need so older data moves to the cheap magnetic tier, batch writes to reduce per-write overhead, and scope queries tightly with time-range and dimension filters so they scan less data. Retention tuning is the biggest lever.

Why is the Timestream memory store expensive?

The memory store holds recent data for fast queries and is billed per GB-hour, far more than the magnetic store's per-GB-month rate. Keeping data in memory longer than your fast queries need is the common overspend; let older data age into the cheaper magnetic tier.

How are Timestream queries billed?

Per gigabyte scanned, like Athena. Queries that filter tightly on time ranges and dimensions scan less data and cost less, while queries that scan long histories or wide data cost more. Scoping queries to the data actually needed is the query-cost lever.

What are the two Timestream storage tiers?

The memory store, a fast tier for recent data billed per GB-hour, and the magnetic store, a cheaper tier for older data billed per GB-month. Data moves from memory to magnetic based on the retention window you configure, so tuning that window balances query speed against cost.

Does C3X estimate Timestream cost?

Timestream cost is driven by write volume, storage retention across tiers, and data scanned by queries, which are usage inputs. C3X prices the surrounding infrastructure, and you model these to estimate the time-series database charges.

What to do next

Estimate the infrastructure around your time-series data before you build it. C3X reads your Terraform and prices your resources against a live catalog. Start with the quickstart.