Build Timestream table configurations with memory/magnetic retention policies, partition keys, and write settings.
Build Timestream table configurations with memory/magnetic retention policies, partition keys, and write settings.
Required Fields
DatabaseNameTableNameRetentionPropertiesOutput will appear here...Build a Timestream table with separate memory-store and magnetic-store retention windows: MemoryStoreRetentionPeriodInHours (24 hours in the example) keeps the most recent data on fast, expensive storage for low-latency queries, while data automatically ages out into the cheaper MagneticStoreRetentionPeriodInDays (365 days) tier. CompositePartitionKey with a DIMENSION-type key set to REQUIRED enforcement is a schema-design decision made largely at table-creation time, choosing the wrong partition key dimension (one with poor cardinality distribution for your query patterns) hurts both write throughput and query performance in ways that are expensive to fix after significant data has accumulated.
Get the CompositePartitionKey choice right before significant data accumulates, it's a table-creation-time decision that's expensive to undo (create new table, migrate data) once real query patterns reveal the original choice was suboptimal.
Route rejected records to an S3 destination via MagneticStoreWriteProperties from day one, without it, malformed writes just fail with no record of what was rejected, making a client-side data-quality bug much harder to diagnose after the fact.
MemoryStoreRetentionPeriodInHours should track your actual hot-query window, not be set arbitrarily large 'to be safe', since memory store is meaningfully more expensive per GB than magnetic store, an oversized memory retention window is a direct, ongoing cost inflation.
The builder validates that DatabaseName, TableName, and RetentionProperties all resolve before accepting the JSON as a valid CreateTable request, the fields Timestream needs to place the table in a database with defined retention tiers; it can't verify the referenced database actually exists or that the partition key dimension choice is well-suited to your actual query patterns, that's a design judgment call, not something schema validation catches.
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