Amazon DynamoDB
A fully managed NoSQL database service provided by AWS, offering high performance and scalability. It is suited for applications requiring low-latency access and large-scale data storage.
Timeline (last 90 days)
DynamoDB's Scan operation reads through every record in the table, and using a filter expression does not reduce the cost of the Scan.
In DynamoDB, if a large number of records share the same partition key value, they will be concentrated into the same internal physical partition and be constrained by that partition's throughput limit, easily causing single-partition hot spots and throughput bottlenecks; when choosing a partition key, values should be spread out as much as possible, for example by using a user ID or a random suffix.
The DynamoDB CLI writes items using typed JSON, with strings written as {"S": "..."} and numbers as {"N": "2"}; the numeric value itself is transmitted as a string, and writing {"N": 2} is incorrect.
DynamoDB's PutItem will not raise an error or warning for two writes to the same primary key; the second write completely replaces the record from the first write, including its attributes (rather than adding a second record).
A single DynamoDB item currently has a 400 KB size limit, and there are also limits on the depth of nested attributes; the database does not validate the type or existence of non-key attributes, so the application layer must ensure consistency itself.
DynamoDB's GetItem takes a complete primary key and returns the corresponding single record (or nothing), and adding `--return-consumed-capacity TOTAL` displays the read capacity consumed by that request.
DynamoDB reads are eventually consistent by default; adding `--consistent-read` makes them strongly consistent reads that reflect all previously completed writes, but the consumed read capacity cost doubles.
DynamoDB is a service accessed entirely through APIs, and all operations can be done in the terminal via the AWS CLI.
The partition key chosen when creating a table determines both which record each write lands on and how much work each read does; reading by key goes straight to a single record, while Scan reads through all records.
DynamoDB's on-demand capacity mode charges per read and write request with no need to plan capacity in advance; the official documentation calls it the default and recommended mode, and no throughput is charged when a table has no traffic, with storage billed separately.
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All Facts (20)
Mainstream distributed databases such as Amazon DynamoDB and Apache Cassandra typically choose the AP combination (availability + partition tolerance) and use tunable consistency levels to meet different business scenarios.
60%UnverifiedDynamoDB's Scan operation reads through every record in the table, and using a filter expression does not reduce the cost of the Scan.
50%UnverifiedThe DynamoDB CLI writes items using typed JSON, with strings written as {"S": "..."} and numbers as {"N": "2"}; the numeric value itself is transmitted as a string, and writing {"N": 2} is incorrect.
50%UnverifiedDynamoDB's PutItem will not raise an error or warning for two writes to the same primary key; the second write completely replaces the record from the first write, including its attributes (rather than adding a second record).
50%UnverifiedA single DynamoDB item currently has a 400 KB size limit, and there are also limits on the depth of nested attributes; the database does not validate the type or existence of non-key attributes, so the application layer must ensure consistency itself.
50%UnverifiedDynamoDB's GetItem takes a complete primary key and returns the corresponding single record (or nothing), and adding `--return-consumed-capacity TOTAL` displays the read capacity consumed by that request.
50%UnverifiedDynamoDB reads are eventually consistent by default; adding `--consistent-read` makes them strongly consistent reads that reflect all previously completed writes, but the consumed read capacity cost doubles.
50%UnverifiedDynamoDB is a service accessed entirely through APIs, and all operations can be done in the terminal via the AWS CLI.
50%UnverifiedThe partition key chosen when creating a table determines both which record each write lands on and how much work each read does; reading by key goes straight to a single record, while Scan reads through all records.
50%UnverifiedDynamoDB's on-demand capacity mode charges per read and write request with no need to plan capacity in advance; the official documentation calls it the default and recommended mode, and no throughput is charged when a table has no traffic, with storage billed separately.
50%UnverifiedAs of 2026-10-02, the DynamoDB pricing page lists 25 GB of free storage per region, plus 25 free read capacity units and 25 free write capacity units, but the latter apply only to provisioned mode, not to on-demand requests.
50%UnverifiedIn provisioned mode, 1 RCU represents one strongly consistent read per second of a 4 KB item, or two eventually consistent reads per second; 1 WCU represents 1 KB written per second; when an item exceeds the threshold it rounds up and consumes multiple units.
50%UnverifiedA DynamoDB table is a collection of items, each item being a set of attributes; each item must have a unique primary key, in the simplest case the primary key is just a partition key, and DynamoDB feeds the partition key value into an internal hash function to determine where the item is stored.
50%UnverifiedWhen creating a DynamoDB table, `--attribute-definitions` only needs to list the key attributes; apart from the keys the table is schemaless, and each record can carry different attributes; key attributes must be of string, number, or binary type.
50%UnverifiedIn DynamoDB, if a large number of records share the same partition key value, they will be concentrated into the same internal physical partition and be constrained by that partition's throughput limit, easily causing single-partition hot spots and throughput bottlenecks; when choosing a partition key, values should be spread out as much as possible, for example by using a user ID or a random suffix.
50%UnverifiedDurable Functions enable functions to sleep at any point and resume when conditions are met by introducing a persistent execution history (stored in a backend such as Amazon DynamoDB), preserving complete context and local variables.
50%UnverifiedAmazon DynamoDB is responsible for storing the agent's state data and task records, providing a high-performance and scalable persistence layer.
50%UnverifiedImplementing the ask_human tool requires serializing and persisting the agent's execution state to DynamoDB, suspending execution, and resuming after human feedback, forming a suspend-resume pattern.
50%UnverifiedCosmos DB is a document-oriented multi-model database supporting tunable consistency levels; DynamoDB is a hybrid key-value/document model; Cloud Spanner is a distributed relational database offering external strong consistency and full SQL support.
50%UnverifiedMicrosoft's multi-cloud database SDK for Java entered public preview, providing a unified CRUD and query API usable across Azure Cosmos DB, Amazon DynamoDB, and Google Cloud Spanner.
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