DynamoDB Streams
E427710
DynamoDB Streams is a change data capture feature of Amazon DynamoDB that records item-level modifications in near real time for use cases like event-driven processing, replication, and auditing.
All labels observed (2)
| Label | Occurrences |
|---|---|
| Amazon DynamoDB Streams | 1 |
| DynamoDB Streams canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4279892 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DynamoDB Streams Context triple: [Amazon DynamoDB, supportsFeature, DynamoDB Streams]
-
A.
Amazon DynamoDB
Amazon DynamoDB is a fully managed, serverless NoSQL database service by AWS designed for high-performance, scalable key-value and document data storage.
-
B.
Amazon Kinesis
Amazon Kinesis is a fully managed AWS service for real-time collection, processing, and analysis of streaming data at scale.
-
C.
Amazon Kinesis Data Firehose
Amazon Kinesis Data Firehose is a fully managed AWS service for reliably capturing, transforming, and loading real-time streaming data into data lakes, warehouses, and analytics services.
-
D.
Amazon DocumentDB
Amazon DocumentDB is a fully managed, scalable document database service from AWS designed to be compatible with MongoDB workloads and optimized for performance, durability, and security in the cloud.
-
E.
Amazon Redshift
Amazon Redshift is a fully managed, cloud-based data warehousing service from Amazon Web Services designed for fast querying and analysis of large datasets using SQL.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DynamoDB Streams Target entity description: DynamoDB Streams is a change data capture feature of Amazon DynamoDB that records item-level modifications in near real time for use cases like event-driven processing, replication, and auditing.
-
A.
Amazon DynamoDB
Amazon DynamoDB is a fully managed, serverless NoSQL database service by AWS designed for high-performance, scalable key-value and document data storage.
-
B.
Amazon Kinesis
Amazon Kinesis is a fully managed AWS service for real-time collection, processing, and analysis of streaming data at scale.
-
C.
Amazon Kinesis Data Firehose
Amazon Kinesis Data Firehose is a fully managed AWS service for reliably capturing, transforming, and loading real-time streaming data into data lakes, warehouses, and analytics services.
-
D.
Amazon Kinesis Data Analytics
Amazon Kinesis Data Analytics is a fully managed AWS service that enables real-time processing and analysis of streaming data using SQL or Apache Flink.
-
E.
Amazon EventBridge
Amazon EventBridge is a serverless event bus service from AWS that enables applications to connect using events from AWS services, integrated SaaS applications, and custom sources for event-driven architectures.
- F. None of above. chosen
Statements (53)
| Predicate | Object |
|---|---|
| instanceOf |
AWS service feature
ⓘ
change data capture system ⓘ |
| accessedVia |
AWS CLI
NERFINISHED
ⓘ
AWS SDKs NERFINISHED ⓘ DynamoDB Streams API NERFINISHED ⓘ |
| billingModel |
charged per read request unit on stream
ⓘ
pay-per-request ⓘ |
| canBe |
disabled on a DynamoDB table
ⓘ
enabled on a DynamoDB table ⓘ |
| configurationScope | per-table setting ⓘ |
| deliveryModel | pull-based consumption ⓘ |
| developedBy | Amazon Web Services NERFINISHED ⓘ |
| exposes |
sequence numbers
ⓘ
shards ⓘ |
| granularity | per-item changes ⓘ |
| integratesWith |
AWS Glue
NERFINISHED
ⓘ
AWS Kinesis Data Streams applications NERFINISHED ⓘ AWS Lambda NERFINISHED ⓘ Amazon OpenSearch Service via pipelines ⓘ Kinesis Client Library NERFINISHED ⓘ |
| ordering | per-partition key order ⓘ |
| partOf | Amazon DynamoDB NERFINISHED ⓘ |
| predicateType | optional feature ⓘ |
| provides | near real-time change data capture ⓘ |
| records | item-level modifications ⓘ |
| regionScope | regional service ⓘ |
| requires | idempotent consumers for exactly-once effects ⓘ |
| retentionPeriod |
24 hours
ⓘ
up to 24 hours of stream records ⓘ |
| stores | stream records ⓘ |
| streamRecordContains |
approximate creation timestamp
ⓘ
event name ⓘ keys of the item ⓘ new image of the item ⓘ old image of the item ⓘ |
| supports |
CloudWatch metrics for stream activity
ⓘ
IAM-based access control ⓘ at-least-once delivery semantics ⓘ encryption at rest via DynamoDB encryption ⓘ insert events ⓘ modify events ⓘ remove events ⓘ |
| supportsViewType |
KEYS_ONLY
ⓘ
NEW_AND_OLD_IMAGES ⓘ NEW_IMAGE ⓘ OLD_IMAGE ⓘ |
| usedFor |
auditing
ⓘ
cross-region replication ⓘ data replication ⓘ event-driven processing ⓘ materialized view maintenance ⓘ microservices integration ⓘ triggering AWS Lambda functions ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: DynamoDB Streams Description of subject: DynamoDB Streams is a change data capture feature of Amazon DynamoDB that records item-level modifications in near real time for use cases like event-driven processing, replication, and auditing.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.
this entity surface form:
Amazon DynamoDB Streams