Kinesis Data Firehose

This page describes how Kinesis Data Firehose maps to services in the environment where the application runs. Some profiles adapt origin API calls; others translate infrastructure or document target-native behavior.

Supported environments

Environment	Mapping
Akamai	Mapped
Azure	API
DigitalOcean	API
Google Cloud	API
OCI	API
Private Kubernetes	API
Scaleway	Mapped

API means the profile adapts origin API behavior. Infrastructure means the profile changes provisioned resources or documents a target-native alternative without promising an origin API endpoint. Check the operation and capability tables for the behavior your application depends on.

How the targets compare

Each row compares a capability of Kinesis Data Firehose with its adaptation on each target. A dash means this profile does not state the capability for that target.

Cloud Adapter

Capability	Kinesis Data Firehose	Akamai, DigitalOcean, Google Cloud, Private Kubernetes, and Scaleway · Strimzi Kafka	Azure	DigitalOcean · DigitalOcean Managed Kafka	Google Cloud · Google Pub/Sub	OCI
Ingest (Direct PUT)	PutRecord / PutRecordBatch	buffered onto Apache Kafka (Strimzi) on the target cluster	buffered onto Azure Event Hubs	buffered onto DigitalOcean Managed Kafka	buffered onto Google Cloud Pub/Sub	buffered onto OCI Streaming
Record transformation · per-batch	Lambda	the Lambda equivalent	the Lambda equivalent	the Lambda equivalent	the Lambda equivalent	the Lambda equivalent
Delivery sink · destination API	S3 / Redshift / OpenSearch / Snowflake / Splunk / Datadog / HTTP	Records are delivered through destination APIs; warehouse delivery is a record-loading integration, not a Redshift service replacement.	Records are delivered through destination APIs; warehouse delivery is a record-loading integration, not a Redshift service replacement.	Records are delivered through destination APIs; warehouse delivery is a record-loading integration, not a Redshift service replacement.	Records are delivered through destination APIs; warehouse delivery is a record-loading integration, not a Redshift service replacement.	Records are delivered through destination APIs; warehouse delivery is a record-loading integration, not a Redshift service replacement.
Format conversion	Yes	Partial - JSON→Parquet served against a default/inferred schema; the declared Glue Data Catalog schema is AWS-specific and has no target counterpart	Partial - JSON→Parquet served against a default/inferred schema; the declared Glue Data Catalog schema is AWS-specific and has no target counterpart	Partial - JSON→Parquet served against a default/inferred schema; the declared Glue Data Catalog schema is AWS-specific and has no target counterpart	Partial - JSON→Parquet served against a default/inferred schema; the declared Glue Data Catalog schema is AWS-specific and has no target counterpart	Partial - JSON→Parquet served against a default/inferred schema; the declared Glue Data Catalog schema is AWS-specific and has no target counterpart
Snowflake / Splunk / Datadog sinks	Yes	Yes - delivered to Snowpipe / HEC / intake endpoints from the target cloud	Yes - delivered to Snowpipe / HEC / intake endpoints from the target cloud	Yes - delivered to Snowpipe / HEC / intake endpoints from the target cloud	Yes - delivered to Snowpipe / HEC / intake endpoints from the target cloud	Yes - delivered to Snowpipe / HEC / intake endpoints from the target cloud
Redshift sink	Yes	Partial - A retained Redshift destination or a destination-specific warehouse loader; no database, schema or SQL migration	Partial - A retained Redshift destination or a destination-specific warehouse loader; no database, schema or SQL migration	Partial - A retained Redshift destination or a destination-specific warehouse loader; no database, schema or SQL migration	Partial - A retained Redshift destination or a destination-specific warehouse loader; no database, schema or SQL migration	Partial - A retained Redshift destination or a destination-specific warehouse loader; no database, schema or SQL migration
API coverage	full	partial	partial	partial	partial	partial

On Akamai, DigitalOcean, Google Cloud, Private Kubernetes, and Scaleway

Strimzi Kafka

Operation	Area	Support	Depth	Notes
Buffering (size / interval)	Delivery	Supported	Most usage	the buffer size and interval hints drive when a batch flushes to the sink
Dynamic partitioning	Delivery	Partial	Full surface	key-based dynamic partitioning of the delivered objects is a subset of Firehose’s grammar
CreateDeliveryStream / DeleteDeliveryStream	Delivery stream	Supported	Common	the delivery stream, its buffering policy, and its sink are provisioned at apply-time
PutRecord / PutRecordBatch (Direct PUT)	Ingest	Supported	Common	records are buffered onto Apache Kafka (Strimzi) on the target cluster; a Kinesis-stream source maps to the Kinesis adapter
Delivery to destination APIs	Sink	Supported	Common	the delivery agent sends records to each configured destination through that service’s API, preserving the destination’s delivery behavior
Sink: Apache Iceberg tables	Sink	Out of scope	Full surface	an Apache Iceberg destination is not offered: Iceberg tables register in the AWS Glue Data Catalog, which is AWS-specific and has no target-native counterpart on these backends
Sink: OpenSearch Serverless	Sink	Partial	Full surface	the AWS serverless collection endpoint is replaced by the target’s OpenSearch or search service, using the same delivery mechanism as the OpenSearch destination
Sink: Redshift (AWS warehouse)	Sink	Partial	Full surface	A retained Redshift destination requires a delivery integration. Moving record delivery to BigQuery, Synapse or ClickHouse requires a destination-specific object-storage load; it does not migrate Redshift schemas, SQL or warehouse behavior.
Sink: S3 / object store, HTTP, OpenSearch	Sink	Supported	Common	the S3 sink bridges to the Cloud Adapter deployment object store (MinIO) (the target object store); an HTTP-endpoint sink forwards natively; an OpenSearch sink bridges to the target’s OpenSearch/Elasticsearch equivalent
Sink: Snowflake / Splunk / Datadog (SaaS)	Sink	Supported	Most usage	records are sent to Snowflake Snowpipe, Splunk HTTP Event Collector (HEC), or Datadog’s intake API. These endpoints can receive records from the target cloud
Format conversion (JSON → Parquet)	Transform	Partial	Full surface	JSON→Parquet conversion uses a default or inferred schema. The declared AWS Glue Data Catalog schema is not translated, so conversion does not use your Glue table definition
Record transformation (Lambda)	Transform	Supported	Most usage	a transform runs each batch through the Lambda equivalent before delivery

Acceptance, buffering and delivery

The application sends Firehose PutRecord or PutRecordBatch requests to the Tensor9 adapter. The mapping buffers accepted records on Apache Kafka (Strimzi) on the target cluster, then a delivery worker sends batches to the configured destination. The object-storage destination for this mapping is the Cloud Adapter deployment object store (MinIO). Success from the ingest API means acceptance into the buffer, not confirmation from the final destination. Inspect individual results when a batch has both successful and failed records. Size and interval settings control when a batch is ready for delivery. A low-volume stream may wait for the interval; a busy stream may reach the size threshold first. Worker scheduling, optional transformation and destination response time also affect delivery latency, so the buffering interval is not an end-to-end latency guarantee.

Transformation and destination setup

The intended delivery path can run a batch through the selected Lambda adapter before writing its output. JSON-to-Parquet conversion uses a default or inferred schema; it does not import the declared Glue table schema. Validate field types and the resulting files with their readers. HTTP, search and SaaS destinations require their own credentials, reachable endpoints and delivery formats. A warehouse loader delivers records to the selected warehouse. Configure its destination tables and load format separately; this mapping does not migrate a Redshift database, schema, SQL queries or warehouse workload.

Failure recovery and migration

Delivery must tolerate a destination accepting a batch before the worker records success. A retry can therefore repeat records or create a duplicate object. Downstream processing should identify duplicates. Monitor pending work, retry failures and destination delivery, rather than using successful PutRecord calls as a delivery-health signal. Provision destination storage, credentials and transformation dependencies before switching producers. Allow the old AWS stream to finish delivering its buffered records; those pending records are not copied into the new buffer. Test the selected destination with representative batches, including destination failures and retries. Measure delivery delay and sustained throughput with the actual transform, batch settings and destination.

On Azure

Azure Event Hubs

Operation	Area	Support	Depth	Notes
Buffering (size / interval)	Delivery	Supported	Most usage	the buffer size and interval hints drive when a batch flushes to the sink
Dynamic partitioning	Delivery	Partial	Full surface	key-based dynamic partitioning of the delivered objects is a subset of Firehose’s grammar
CreateDeliveryStream / DeleteDeliveryStream	Delivery stream	Supported	Common	the delivery stream, its buffering policy, and its sink are provisioned at apply-time
PutRecord / PutRecordBatch (Direct PUT)	Ingest	Supported	Common	records are buffered onto Azure Event Hubs; a Kinesis-stream source maps to the Kinesis adapter
Delivery to destination APIs	Sink	Supported	Common	the delivery agent sends records to each configured destination through that service’s API, preserving the destination’s delivery behavior
Sink: Apache Iceberg tables	Sink	Out of scope	Full surface	an Apache Iceberg destination is not offered: Iceberg tables register in the AWS Glue Data Catalog, which is AWS-specific and has no target-native counterpart on these backends
Sink: OpenSearch Serverless	Sink	Partial	Full surface	the AWS serverless collection endpoint is replaced by the target’s OpenSearch or search service, using the same delivery mechanism as the OpenSearch destination
Sink: Redshift (AWS warehouse)	Sink	Partial	Full surface	A retained Redshift destination requires a delivery integration. Moving record delivery to BigQuery, Synapse or ClickHouse requires a destination-specific object-storage load; it does not migrate Redshift schemas, SQL or warehouse behavior.
Sink: S3 / object store, HTTP, OpenSearch	Sink	Supported	Common	the S3 sink bridges to Azure Blob Storage (the target object store); an HTTP-endpoint sink forwards natively; an OpenSearch sink bridges to the target’s OpenSearch/Elasticsearch equivalent
Sink: Snowflake / Splunk / Datadog (SaaS)	Sink	Supported	Most usage	records are sent to Snowflake Snowpipe, Splunk HTTP Event Collector (HEC), or Datadog’s intake API. These endpoints can receive records from the target cloud
Format conversion (JSON → Parquet)	Transform	Partial	Full surface	JSON→Parquet conversion uses a default or inferred schema. The declared AWS Glue Data Catalog schema is not translated, so conversion does not use your Glue table definition
Record transformation (Lambda)	Transform	Supported	Most usage	a transform runs each batch through the Lambda equivalent before delivery

Acceptance, buffering and delivery

The application sends Firehose PutRecord or PutRecordBatch requests to the Tensor9 adapter. The mapping buffers accepted records on Azure Event Hubs, then a delivery worker sends batches to the configured destination. The object-storage destination for this mapping is Azure Blob Storage. Success from the ingest API means acceptance into the buffer, not confirmation from the final destination. Inspect individual results when a batch has both successful and failed records. Size and interval settings control when a batch is ready for delivery. A low-volume stream may wait for the interval; a busy stream may reach the size threshold first. Worker scheduling, optional transformation and destination response time also affect delivery latency, so the buffering interval is not an end-to-end latency guarantee.

Transformation and destination setup

Failure recovery and migration

On DigitalOcean

DigitalOcean Managed Kafka

Operation	Area	Support	Depth	Notes
Buffering (size / interval)	Delivery	Supported	Most usage	the buffer size and interval hints drive when a batch flushes to the sink
Dynamic partitioning	Delivery	Partial	Full surface	key-based dynamic partitioning of the delivered objects is a subset of Firehose’s grammar
CreateDeliveryStream / DeleteDeliveryStream	Delivery stream	Supported	Common	the delivery stream, its buffering policy, and its sink are provisioned at apply-time
PutRecord / PutRecordBatch (Direct PUT)	Ingest	Supported	Common	records are buffered onto DigitalOcean Managed Kafka; a Kinesis-stream source maps to the Kinesis adapter
Delivery to destination APIs	Sink	Supported	Common	the delivery agent sends records to each configured destination through that service’s API, preserving the destination’s delivery behavior
Sink: Apache Iceberg tables	Sink	Out of scope	Full surface	an Apache Iceberg destination is not offered: Iceberg tables register in the AWS Glue Data Catalog, which is AWS-specific and has no target-native counterpart on these backends
Sink: OpenSearch Serverless	Sink	Partial	Full surface	the AWS serverless collection endpoint is replaced by the target’s OpenSearch or search service, using the same delivery mechanism as the OpenSearch destination
Sink: Redshift (AWS warehouse)	Sink	Partial	Full surface	A retained Redshift destination requires a delivery integration. Moving record delivery to BigQuery, Synapse or ClickHouse requires a destination-specific object-storage load; it does not migrate Redshift schemas, SQL or warehouse behavior.
Sink: S3 / object store, HTTP, OpenSearch	Sink	Supported	Common	the S3 sink bridges to DigitalOcean Spaces (the target object store); an HTTP-endpoint sink forwards natively; an OpenSearch sink bridges to the target’s OpenSearch/Elasticsearch equivalent
Sink: Snowflake / Splunk / Datadog (SaaS)	Sink	Supported	Most usage	records are sent to Snowflake Snowpipe, Splunk HTTP Event Collector (HEC), or Datadog’s intake API. These endpoints can receive records from the target cloud
Format conversion (JSON → Parquet)	Transform	Partial	Full surface	JSON→Parquet conversion uses a default or inferred schema. The declared AWS Glue Data Catalog schema is not translated, so conversion does not use your Glue table definition
Record transformation (Lambda)	Transform	Supported	Most usage	a transform runs each batch through the Lambda equivalent before delivery

Acceptance, buffering and delivery

The application sends Firehose PutRecord or PutRecordBatch requests to the Tensor9 adapter. The mapping buffers accepted records on DigitalOcean Managed Kafka, then a delivery worker sends batches to the configured destination. The object-storage destination for this mapping is DigitalOcean Spaces. Success from the ingest API means acceptance into the buffer, not confirmation from the final destination. Inspect individual results when a batch has both successful and failed records. Size and interval settings control when a batch is ready for delivery. A low-volume stream may wait for the interval; a busy stream may reach the size threshold first. Worker scheduling, optional transformation and destination response time also affect delivery latency, so the buffering interval is not an end-to-end latency guarantee.

Transformation and destination setup

Failure recovery and migration

On Google Cloud

Google Pub/Sub

Operation	Area	Support	Depth	Notes
Buffering (size / interval)	Delivery	Supported	Most usage	the buffer size and interval hints drive when a batch flushes to the sink
Dynamic partitioning	Delivery	Partial	Full surface	key-based dynamic partitioning of the delivered objects is a subset of Firehose’s grammar
CreateDeliveryStream / DeleteDeliveryStream	Delivery stream	Supported	Common	the delivery stream, its buffering policy, and its sink are provisioned at apply-time
PutRecord / PutRecordBatch (Direct PUT)	Ingest	Supported	Common	records are buffered onto Google Cloud Pub/Sub; a Kinesis-stream source maps to the Kinesis adapter
Delivery to destination APIs	Sink	Supported	Common	the delivery agent sends records to each configured destination through that service’s API, preserving the destination’s delivery behavior
Sink: Apache Iceberg tables	Sink	Out of scope	Full surface	an Apache Iceberg destination is not offered: Iceberg tables register in the AWS Glue Data Catalog, which is AWS-specific and has no target-native counterpart on these backends
Sink: OpenSearch Serverless	Sink	Partial	Full surface	the AWS serverless collection endpoint is replaced by the target’s OpenSearch or search service, using the same delivery mechanism as the OpenSearch destination
Sink: Redshift (AWS warehouse)	Sink	Partial	Full surface	A retained Redshift destination requires a delivery integration. Moving record delivery to BigQuery, Synapse or ClickHouse requires a destination-specific object-storage load; it does not migrate Redshift schemas, SQL or warehouse behavior.
Sink: S3 / object store, HTTP, OpenSearch	Sink	Supported	Common	the S3 sink bridges to Google Cloud Storage (the target object store); an HTTP-endpoint sink forwards natively; an OpenSearch sink bridges to the target’s OpenSearch/Elasticsearch equivalent
Sink: Snowflake / Splunk / Datadog (SaaS)	Sink	Supported	Most usage	records are sent to Snowflake Snowpipe, Splunk HTTP Event Collector (HEC), or Datadog’s intake API. These endpoints can receive records from the target cloud
Format conversion (JSON → Parquet)	Transform	Partial	Full surface	JSON→Parquet conversion uses a default or inferred schema. The declared AWS Glue Data Catalog schema is not translated, so conversion does not use your Glue table definition
Record transformation (Lambda)	Transform	Supported	Most usage	a transform runs each batch through the Lambda equivalent before delivery

Acceptance, buffering and delivery

The application sends Firehose PutRecord or PutRecordBatch requests to the Tensor9 adapter. The mapping buffers accepted records on Google Cloud Pub/Sub, then a delivery worker sends batches to the configured destination. The object-storage destination for this mapping is Google Cloud Storage. Success from the ingest API means acceptance into the buffer, not confirmation from the final destination. Inspect individual results when a batch has both successful and failed records. Size and interval settings control when a batch is ready for delivery. A low-volume stream may wait for the interval; a busy stream may reach the size threshold first. Worker scheduling, optional transformation and destination response time also affect delivery latency, so the buffering interval is not an end-to-end latency guarantee.

Transformation and destination setup

Failure recovery and migration

On OCI

OCI Streaming

Operation	Area	Support	Depth	Notes
Buffering (size / interval)	Delivery	Supported	Most usage	the buffer size and interval hints drive when a batch flushes to the sink
Dynamic partitioning	Delivery	Partial	Full surface	key-based dynamic partitioning of the delivered objects is a subset of Firehose’s grammar
CreateDeliveryStream / DeleteDeliveryStream	Delivery stream	Supported	Common	the delivery stream, its buffering policy, and its sink are provisioned at apply-time
PutRecord / PutRecordBatch (Direct PUT)	Ingest	Supported	Common	records are buffered onto OCI Streaming; a Kinesis-stream source maps to the Kinesis adapter
Delivery to destination APIs	Sink	Supported	Common	the delivery agent sends records to each configured destination through that service’s API, preserving the destination’s delivery behavior
Sink: Apache Iceberg tables	Sink	Out of scope	Full surface	an Apache Iceberg destination is not offered: Iceberg tables register in the AWS Glue Data Catalog, which is AWS-specific and has no target-native counterpart on these backends
Sink: OpenSearch Serverless	Sink	Partial	Full surface	the AWS serverless collection endpoint is replaced by the target’s OpenSearch or search service, using the same delivery mechanism as the OpenSearch destination
Sink: Redshift (AWS warehouse)	Sink	Partial	Full surface	A retained Redshift destination requires a delivery integration. Moving record delivery to BigQuery, Synapse or ClickHouse requires a destination-specific object-storage load; it does not migrate Redshift schemas, SQL or warehouse behavior.
Sink: S3 / object store, HTTP, OpenSearch	Sink	Supported	Common	the S3 sink bridges to OCI Object Storage (the target object store); an HTTP-endpoint sink forwards natively; an OpenSearch sink bridges to the target’s OpenSearch/Elasticsearch equivalent
Sink: Snowflake / Splunk / Datadog (SaaS)	Sink	Supported	Most usage	records are sent to Snowflake Snowpipe, Splunk HTTP Event Collector (HEC), or Datadog’s intake API. These endpoints can receive records from the target cloud
Format conversion (JSON → Parquet)	Transform	Partial	Full surface	JSON→Parquet conversion uses a default or inferred schema. The declared AWS Glue Data Catalog schema is not translated, so conversion does not use your Glue table definition
Record transformation (Lambda)	Transform	Supported	Most usage	a transform runs each batch through the Lambda equivalent before delivery

Acceptance, buffering and delivery

The application sends Firehose PutRecord or PutRecordBatch requests to the Tensor9 adapter. The mapping buffers accepted records on OCI Streaming, then a delivery worker sends batches to the configured destination. The object-storage destination for this mapping is OCI Object Storage. Success from the ingest API means acceptance into the buffer, not confirmation from the final destination. Inspect individual results when a batch has both successful and failed records. Size and interval settings control when a batch is ready for delivery. A low-volume stream may wait for the interval; a busy stream may reach the size threshold first. Worker scheduling, optional transformation and destination response time also affect delivery latency, so the buffering interval is not an end-to-end latency guarantee.

Transformation and destination setup

Failure recovery and migration

Existing data and credentials

Selecting a backend does not copy existing data, credentials or access policies. Plan and verify migration separately before changing an application’s endpoint. Do not assume an identifier, credential or encrypted value from the origin service works unchanged on the target.

Configure, tune and debug

Start with setup and configuration. Use tuning to understand supported request tags, debugging to investigate a request, and High Fidelity Cloud Emulators to validate a bounded reproduction.

​Supported environments

​How the targets compare

​Cloud Adapter

​On Akamai, DigitalOcean, Google Cloud, Private Kubernetes, and Scaleway

​Strimzi Kafka

​Acceptance, buffering and delivery

​Transformation and destination setup

​Failure recovery and migration

​On Azure

​Azure Event Hubs

​Acceptance, buffering and delivery

​Transformation and destination setup

​Failure recovery and migration

​On DigitalOcean

​DigitalOcean Managed Kafka

​Acceptance, buffering and delivery

​Transformation and destination setup

​Failure recovery and migration

​On Google Cloud

​Google Pub/Sub

​Acceptance, buffering and delivery

​Transformation and destination setup

​Failure recovery and migration

​On OCI

​OCI Streaming

​Acceptance, buffering and delivery

​Transformation and destination setup

​Failure recovery and migration

​Existing data and credentials

​Configure, tune and debug

Supported environments

How the targets compare

Cloud Adapter

On Akamai, DigitalOcean, Google Cloud, Private Kubernetes, and Scaleway

Strimzi Kafka

Acceptance, buffering and delivery

Transformation and destination setup

Failure recovery and migration

On Azure

Azure Event Hubs

Acceptance, buffering and delivery

Transformation and destination setup

Failure recovery and migration

On DigitalOcean

DigitalOcean Managed Kafka

Acceptance, buffering and delivery

Transformation and destination setup

Failure recovery and migration

On Google Cloud

Google Pub/Sub

Acceptance, buffering and delivery

Transformation and destination setup

Failure recovery and migration

On OCI

OCI Streaming

Acceptance, buffering and delivery

Transformation and destination setup

Failure recovery and migration

Existing data and credentials

Configure, tune and debug