Navigation: Dissolve cross-tree references

docs/admin/index.md

@@ -32,10 +32,9 @@ Production and troubleshooting guidelines and system resource considerations.
 
 clustering/index
 sharding-partitioning
-../performance/index
 ```
 +++
-Best practices and tips for clustering, sharding, partitioning, and performance tuning.
+Best practices and tips for clustering, sharding, and partitioning.
 ::::
 
 ::::{grid-item-card} {material-outlined}`system_update_alt;2em` Software Upgrades

docs/start/index.md

@@ -117,7 +117,7 @@ first-steps
 going-further
 modelling/index
 query/index
-Ingesting data <../ingest/index>
+ingest
 application/index
 ```
 

docs/start/ingest.md

@@ -0,0 +1,38 @@
+(start-ingest)=
+# Ingesting data
+
+:::{rubric} Features
+:::
+
+The platform supports loading data through native methods such as the
+`COPY FROM` SQL statement, enabling import from local files or remote sources
+including HTTP, FTP, and cloud storage providers like AWS S3 and Azure.
+
+Supported formats for ingestion include CSV and JSON Lines, and CrateDB offers
+features for both batch and incremental loads. Additionally, the Foreign Data
+Wrapper feature allows you to access and query external databases as if they
+were local tables, further expanding integration capabilities.
+
+:::{rubric} Integrations
+:::
+
+The guide also highlights advanced options like using third-party tools and
+connectors—such as ingestr—to migrate or synchronise data from a wide array
+of traditional databases, cloud warehouses, message brokers, and file/object
+storage systems.
+
+These integrations help automate and streamline the ETL (extract, transform,
+load) process, supporting use cases that range from one-time migrations to
+continuous, real-time data pipelines. As a result, CrateDB is well-suited
+for large-scale analytics, IoT, and time-series workloads that demand
+seamless and flexible ingestion strategies.
+
+:::{rubric} Next step
+:::
+
+:::{card} All data ingestion methods for CrateDB at a glance
+:link: ingest
+:link-type: ref
+CrateDB's data ingestion guide provides an overview of how to efficiently bring
+data from various sources into CrateDB.
+:::

docs/start/modelling/fulltext.md

@@ -147,7 +147,7 @@ constraints, all in one.
 
 ## Further Learning & Resources
 
-* [**Full-text Search**](../../feature/search/fts/index.md): In-depth
+* {ref}`Full-text Search <fulltext-search>`: In-depth
   walkthrough of full-text search capabilities.
 * Reference Manual:
   * {ref}`Full-text indices <crate-reference:fulltext-indices>`: Defining
@@ -156,5 +156,8 @@ constraints, all in one.
     analyzers, tokenizers, token and char filters.
   * {ref}`SQL MATCH predicate <crate-reference:sql_dql_fulltext_search>`:
     Details about MATCH predicate arguments and options.
-* [**Hands‑On Academy Course**](https://learn.cratedb.com/cratedb-fundamentals?lesson=fulltext-search):
+* [Hands‑On Academy Course]:
   explore FTS on real datasets (e.g. Chicago neighborhoods).
+
+
+[Hands‑On Academy Course]: https://learn.cratedb.com/cratedb-fundamentals?lesson=fulltext-search

docs/start/query/index.md

@@ -48,7 +48,7 @@ CrateDB is not just a real-time analytics database, it’s a powerful platform t
 
 aggregations
 ad-hoc
-../../feature/search/index
+search
 ai-integration
 Performance <performance>
 ```

docs/start/query/search.md

@@ -0,0 +1,34 @@
+(start-search)=
+# Search
+
+:::{rubric} Features
+:::
+
+CrateDB offers robust search capabilities by combining native full-text,
+geospatial, vector, and hybrid search—all accessible through standard SQL
+queries. At its core, CrateDB leverages Apache Lucene and the BM25 ranking
+algorithm for high-performance full-text search, making it well-suited for
+large-scale, complex information retrieval tasks.
+
+Geospatial and vector search are also natively supported, enabling use cases
+ranging from text analytics to AI/ML and location-based queries, all within
+the same unified platform.
+
+:::{rubric} Hybrid search
+:::
+
+Hybrid search in CrateDB allows you to combine multiple search methods—such
+as term-based, vector, and geospatial—within a single query for powerful
+information discovery. This versatility, together with horizontal
+scalability and SQL compatibility, makes CrateDB an exceptional choice for
+organisations wanting to run advanced search and analytics on diverse data
+types, including structured, semi-structured, and unstructured content.
+
+:::{rubric} Next step
+:::
+
+:::{card} All search features of CrateDB at a glance
+:link: search-overview
+:link-type: ref
+CrateDB provides full-text, geospatial, and vector search natively.
+:::