23 DynamoDB Operations

DynamoDB gives you a small set of operations and expects you to compose everything else out of them. There is no TRUNCATE, no join and no schema to read back. This page lists the operations people reach for most, grouped by what they act on, with a guide for each one.

Table operations

Creating and removing tables, and clearing one out without deleting it.

Create a table. Set the partition key, sort key and indexes, then create the table.
Delete a table. Drop a table and everything in it. There is no undo, so check the name first.
Delete all items. Empty a table but keep its keys, indexes and settings. DynamoDB has no TRUNCATE.

Item operations

Reading and changing the records inside a table.

Query a table. Build a query against a key or an index and get the SDK code for it.
Add an item. Write a new record, including nested maps and lists, without hand-writing the type wrappers.
Update an item. Change attributes on a record in place rather than overwriting the whole item.
Delete an item. Remove a single record by its key.
Conditional write and update. Only write when a condition holds, which is how you avoid clobbering concurrent changes.

Import and export

Getting data in and out, in the formats teams actually use.

Import CSV. Load a spreadsheet export into a table.
Import JSON. Load plain JSON without converting it to DynamoDB JSON first.
Export to CSV. Pull a table or a query result out as a spreadsheet.
Export to JSON. Export records as JSON for backups or for seeding another table.
Export to S3. Send a table to a bucket, which is the route for large exports and analytics.

Design and modelling

Deciding on keys and access patterns before you write any data.

Data modelling. Work out entities and access patterns visually instead of on a whiteboard.
Single-table design. Model several entities into one table and see how the keys overlap.
Schema explorer. See the attributes a table actually contains, which DynamoDB itself will not tell you.

Querying and search

Other ways to get at the data once it is in.

Use SQL with DynamoDB. Query with PartiQL when SQL is the shape you think in.
Semantic and vector search. Search by meaning rather than by exact key match.
JSON path filtering. Filter into nested attributes without writing an expression by hand.
Compare two items. See exactly what differs between two records.

Local and developer tooling

Working against a local instance, and driving DynamoDB from code.

DynamoDB Local admin GUI. Browse and edit a local instance the same way as a real table.
Built-in terminal. Run commands against the table you are looking at.
MCP server for AI tools. Let an AI assistant read and query your tables through MCP.

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