diff --git a/docs/admin/index.md b/docs/admin/index.md index 687cb534..64ed6dfe 100644 --- a/docs/admin/index.md +++ b/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 diff --git a/docs/start/index.md b/docs/start/index.md index c71a511f..adb5883d 100644 --- a/docs/start/index.md +++ b/docs/start/index.md @@ -117,7 +117,7 @@ first-steps going-further modelling/index query/index -Ingesting data <../ingest/index> +ingest application/index ``` diff --git a/docs/start/ingest.md b/docs/start/ingest.md new file mode 100644 index 00000000..1c06c38a --- /dev/null +++ b/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. +::: diff --git a/docs/start/modelling/fulltext.md b/docs/start/modelling/fulltext.md index 75e8c9b8..6751f77e 100644 --- a/docs/start/modelling/fulltext.md +++ b/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 `: In-depth walkthrough of full-text search capabilities. * Reference Manual: * {ref}`Full-text indices `: Defining @@ -156,5 +156,8 @@ constraints, all in one. analyzers, tokenizers, token and char filters. * {ref}`SQL MATCH predicate `: 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 diff --git a/docs/start/query/index.md b/docs/start/query/index.md index 3435605f..051f7b38 100644 --- a/docs/start/query/index.md +++ b/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 ``` diff --git a/docs/start/query/search.md b/docs/start/query/search.md new file mode 100644 index 00000000..e10d07d3 --- /dev/null +++ b/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. +:::