Integrate: Naming things. Adjust reference labels.

Let's also use canonical, non-prefixed variants for the reference
labels. This patch aggressively prunes previous nomenclature to create
less confusion for future authors. If anything breaks on this, it is
now the right time to fix forward.

Author: amotl

docs/ingest/cdc/index.md

@@ -23,15 +23,15 @@ Native and specialized integration connectors for CrateDB, both managed and unma
 :gutter: 2
 
 ::::{grid-item-card} Amazon DynamoDB
-:link: aws-dynamodb
+:link: dynamodb
 :link-type: ref
 Load data from DynamoDB, a fully managed NoSQL database service provided by
 Amazon Web Services (AWS), which is designed for high-performance, scalable
 applications and offers key-value and document data structures.
 ::::
 
 ::::{grid-item-card} Amazon Kinesis
-:link: aws-kinesis
+:link: kinesis
 :link-type: ref
 Load data from Amazon Kinesis Data Streams, a serverless streaming data service
 that simplifies the capture, processing, and storage of data streams at any scale.
@@ -56,7 +56,7 @@ both managed and unmanaged.
 :gutter: 2
 
 ::::{grid-item-card} AWS DMS
-:link: aws-dms
+:link: dms
 :link-type: ref
 Use AWS Database Migration Service (AWS DMS), a managed migration and replication
 service that helps move your database and analytics workloads between different

docs/ingest/etl/index.md

@@ -27,29 +27,23 @@ outlines how to use them effectively. Additionally, see support for {ref}`cdc` s
 
 
 ::::{grid-item-card} {material-outlined}`air;2em` Dataflow / Pipeline / Code-first
-- {ref}`apache-airflow`
+- {ref}`airflow`
 
   Apache Airflow is an open-source software platform to programmatically author,
   schedule, and monitor workflows. Pipelines are defined in Python, allowing for
   dynamic pipeline generation and on-demand, code-driven pipeline invocation.
 
-- {ref}`apache-flink`
-
-  Apache Flink is a programming framework and distributed processing engine for
-  stateful computations over unbounded and bounded data streams, written in Java.
-
-- {ref}`apache-nifi`
-
-  Apache NiFi is a dataflow system based on the concepts of flow-based programming.
-  It supports powerful and scalable directed graphs of data routing, transformation,
-  and system mediation logic.
-
 - {ref}`dbt`
 
   dbt is an SQL-first platform for transforming data in data warehouses using
   Python and SQL. The data abstraction layer provided by dbt-core allows the
   decoupling of the models on which reports and dashboards rely from the source data.
 
+- {ref}`flink`
+
+  Apache Flink is a programming framework and distributed processing engine for
+  stateful computations over unbounded and bounded data streams, written in Java.
+
 - {ref}`kestra`
 
   Kestra is an open-source workflow automation and orchestration toolkit with a rich
@@ -63,23 +57,29 @@ outlines how to use them effectively. Additionally, see support for {ref}`cdc` s
   the Singer specification. Singer is a composable open-source ETL framework and
   specification, including powerful data extraction and consolidation elements.
 
+- {ref}`nifi`
+
+  Apache NiFi is a dataflow system based on the concepts of flow-based programming.
+  It supports powerful and scalable directed graphs of data routing, transformation,
+  and system mediation logic.
+
 +++
 Use data pipeline programming frameworks and platforms.
 ::::
 
 
 ::::{grid-item-card} {material-outlined}`all_inclusive;2em` Low-code / No-code / Visual
-- {ref}`apache-hop`
-
-  Apache Hop aims to be the future of data integration. Visual development enables
-  developers to be more productive than they can be through code.
-
 - {ref}`estuary`
 
   Estuary provides real-time data integration and modern ETL and ELT data pipelines
   as a fully managed solution. Estuary Flow is a real-time, reliable change data
   capture (CDC) solution.
 
+- {ref}`hop`
+
+  Apache Hop aims to be the future of data integration. Visual development enables
+  developers to be more productive than they can be through code.
+
 - {ref}`n8n`
 
   n8n is a workflow automation tool that helps you to connect any app with an API with
@@ -97,13 +97,13 @@ Use visual data flow and integration frameworks and platforms.
 
 
 ::::{grid-item-card} {material-outlined}`storage;2em` Databases
-- {ref}`aws-dms`
+- {ref}`dms`
 
   AWS DMS is a managed migration and replication service that helps move your
   database and analytics workloads between different kinds of databases quickly,
   securely, and with minimal downtime and zero data loss.
 
-- {ref}`aws-dynamodb`
+- {ref}`dynamodb`
 
   DynamoDB is a fully managed NoSQL database service provided by Amazon Web Services (AWS).
 
@@ -132,13 +132,13 @@ Load data from database systems.
 
 
 ::::{grid-item-card} {material-outlined}`fast_forward;2em` Streams
-- {ref}`apache-kafka`
+- {ref}`kafka`
 
   Apache Kafka is an open-source distributed event streaming platform
   for high-performance data pipelines, streaming analytics, data integration,
   and mission-critical applications.
 
-- {ref}`aws-kinesis`
+- {ref}`kinesis`
 
   Amazon Kinesis Data Streams is a serverless streaming data service that simplifies
   the capture, processing, and storage of data streams at any scale, such as
@@ -186,7 +186,7 @@ Use serverless compute units for custom import tasks.
 
 ::::{grid-item-card} {material-outlined}`dataset;2em` Datasets
 
-- {ref}`apache-iceberg`
+- {ref}`iceberg`
 
   Apache Iceberg is an open table format for analytic datasets.
 
@@ -202,25 +202,25 @@ Load data from datasets and open table formats.
 :::
 
 :::{div}
-- {ref}`apache-airflow`
-- {ref}`apache-flink`
-- {ref}`apache-hop`
-- {ref}`apache-iceberg`
-- {ref}`apache-kafka`
-- {ref}`apache-nifi`
-- {ref}`aws-dynamodb`
-- {ref}`aws-kinesis`
-- {ref}`aws-dms`
+- {ref}`airflow`
 - {ref}`aws-lambda`
 - {ref}`azure-functions`
 - {ref}`dbt`
+- {ref}`dms`
+- {ref}`dynamodb`
 - {ref}`estuary`
+- {ref}`flink`
+- {ref}`hop`
+- {ref}`iceberg`
 - {ref}`influxdb`
+- {ref}`kafka`
 - {ref}`kestra`
+- {ref}`kinesis`
 - {ref}`meltano`
 - {ref}`mongodb`
 - {ref}`mysql`
 - {ref}`n8n`
+- {ref}`nifi`
 - {ref}`node-red`
 - {ref}`risingwave`
 - {ref}`sql-server`

docs/integrate/airflow/index.md

@@ -1,5 +1,4 @@
 (airflow)=
-(apache-airflow)=
 (astronomer)=
 # Airflow / Astronomer
 

docs/integrate/dbt/index.md

@@ -30,7 +30,7 @@ With dbt, anyone on your data team can safely contribute to production-grade dat
 pipelines.
 
 The idea is that data engineers make source data available to an environment where
-dbt projects run, for example with [Debezium](#debezium) or with [Airflow](#apache-airflow).
+dbt projects run, for example with {ref}`debezium` or with {ref}`airflow`.
 Afterwards, data analysts can run their dbt projects against this data to produce models
 (tables and views) that can be used with a number of [BI tools](#bi-tools).
 

docs/integrate/dms/index.md

@@ -1,5 +1,4 @@
-(aws-dms)=
-(cdc-dms)=
+(dms)=
 # DMS (AWS Database Migration Service)
 
 :::{include} /_include/links.md

docs/integrate/dynamodb/index.md

@@ -1,5 +1,4 @@
-(aws-dynamodb)=
-(cdc-dynamodb)=
+(dynamodb)=
 # DynamoDB
 
 :::{include} /_include/links.md
@@ -38,7 +37,7 @@ servers or infrastructure.
 :::{rubric} Related
 :::
 - [Amazon DynamoDB Streams]
-- {ref}`aws-kinesis`
+- {ref}`kinesis`
 - [Amazon Kinesis Data Streams]
 ::::
 

docs/integrate/estuary/index.md

@@ -1,5 +1,4 @@
 (estuary)=
-
 # Estuary
 
 ```{div} .float-right

docs/integrate/flink/index.md

@@ -1,4 +1,3 @@
-(apache-flink)=
 (flink)=
 # Flink
 

docs/integrate/hop/index.md

@@ -1,4 +1,4 @@
-(apache-hop)=
+(hop)=
 # Hop
 
 ```{div} .float-right

docs/integrate/iceberg/index.md

@@ -1,4 +1,4 @@
-(apache-iceberg)=
+(iceberg)=
 # Iceberg
 
 ```{div} .float-right