diff --git a/docs/_include/links.md b/docs/_include/links.md index c7ead5fb..d1d06823 100644 --- a/docs/_include/links.md +++ b/docs/_include/links.md @@ -1,6 +1,7 @@ +[ADBC]: https://arrow.apache.org/docs/format/ADBC.html [Admin UI]: inv:crate-admin-ui:*:label#index [Amazon DynamoDB Streams]: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Streams.html [Amazon Kinesis Data Streams]: https://docs.aws.amazon.com/streams/latest/dev/introduction.html @@ -16,6 +17,7 @@ [CrateDB BLOBs]: inv:crate-reference:*:label#blob_support [CrateDB Cloud]: inv:cloud:*:label#index [CrateDB Cloud Console]: https://console.cratedb.cloud/ +[CrateDB Examples]: https://github.com/crate/cratedb-examples [CrateDB JDBC Driver]: https://cratedb.com/docs/jdbc/ [CrateDB Reference Manual]: inv:crate-reference:*:label#index [CrateDB Self-Managed]: https://cratedb.com/product/self-managed @@ -37,9 +39,11 @@ [HNSW paper]: https://arxiv.org/pdf/1603.09320 [HoloViews]: https://www.holoviews.org/ [HoloViz]: https://holoviz.org/ +[HTTP protocol]: https://en.wikipedia.org/wiki/HTTP [Indexing, Columnar Storage, and Aggregations]: https://cratedb.com/product/features/indexing-columnar-storage-aggregations [InfluxDB]: https://github.com/influxdata/influxdb [inverted index]: https://en.wikipedia.org/wiki/Inverted_index +[JDBC]: https://en.wikipedia.org/wiki/Java_Database_Connectivity [JOIN]: inv:crate-reference#sql_joins [JSON Database]: https://cratedb.com/solutions/json-database [kNN]: https://en.wikipedia.org/wiki/K-nearest_neighbor_algorithm @@ -60,7 +64,9 @@ [Multi-model Database]: https://cratedb.com/solutions/multi-model-database [nearest neighbor search]: https://en.wikipedia.org/wiki/Nearest_neighbor_search [Nested Data Structure]: https://cratedb.com/product/features/nested-data-structure +[ODBC]: https://en.wikipedia.org/wiki/Open_Database_Connectivity [PostgreSQL JDBC Driver]: https://jdbc.postgresql.org/ +[PostgreSQL wire protocol]: https://www.postgresql.org/docs/current/protocol.html [python-dbapi-by-example]: inv:crate-python:*:label#by-example [python-sqlalchemy-by-example]: inv:sqlalchemy-cratedb:*:label#by-example [query DSL based on JSON]: https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl.html @@ -69,6 +75,7 @@ [Replicating CDC events from DynamoDB to CrateDB]: https://cratedb.com/blog/replicating-cdc-events-from-dynamodb-to-cratedb [Replicating CDC events to CrateDB using AWS DMS]: https://cratedb.com/blog/replicating-cdc-events-to-cratedb-using-aws-dms [Replicating data to CrateDB with Debezium and Kafka]: https://community.cratedb.com/t/replicating-data-to-cratedb-with-debezium-and-kafka/1388 +[SQL]: https://en.wikipedia.org/wiki/Sql [TF–IDF]: https://en.wikipedia.org/wiki/Tf%E2%80%93idf [timeseries-queries-and-visualization-colab]: https://colab.research.google.com/github/crate/cratedb-examples/blob/main/topic/timeseries/timeseries-queries-and-visualization.ipynb [timeseries-queries-and-visualization-github]: https://github.com/crate/cratedb-examples/blob/main/topic/timeseries/timeseries-queries-and-visualization.ipynb diff --git a/docs/connect/index.md b/docs/connect/index.md index 9752cf59..ab728af4 100644 --- a/docs/connect/index.md +++ b/docs/connect/index.md @@ -45,24 +45,17 @@ protocol. :class: rubric-slim :columns: auto 3 3 3 -```{rubric} Reference Manual +```{rubric} Reference ``` - [HTTP interface] - [PostgreSQL interface] -- [SQL query syntax] -- [Bulk operations] -- [BLOB support][CrateDB BLOBs] - -```{rubric} Protocols and API Standards -``` -- [HTTP protocol] -- [PostgreSQL wire protocol] -- [JDBC] -- [ODBC] -- [SQL] ```{rubric} Related ``` +- [Authentication] +- [SQL query syntax] +- [Bulk operations] +- [BLOB support][CrateDB BLOBs] - {ref}`All drivers ` :::: @@ -193,18 +186,8 @@ All drivers ``` -[ADBC]: https://arrow.apache.org/docs/format/ADBC.html [Authentication]: inv:crate-reference:*:label#admin_auth [Bulk operations]: inv:crate-reference:*:label#http-bulk-ops -[CrateDB Examples]: https://github.com/crate/cratedb-examples [HTTP interface]: inv:crate-reference:*:label#interface-http -[HTTP protocol]: https://en.wikipedia.org/wiki/HTTP -[JDBC]: https://en.wikipedia.org/wiki/Java_Database_Connectivity -[ODBC]: https://en.wikipedia.org/wiki/Open_Database_Connectivity [PostgreSQL interface]: inv:crate-reference:*:label#interface-postgresql -[PostgreSQL wire protocol]: https://www.postgresql.org/docs/current/protocol.html -[schema]: inv:crate-reference:*:label#ddl-create-table-schemas -[schemas]: inv:crate-reference:*:label#ddl-create-table-schemas -[SQL]: https://en.wikipedia.org/wiki/Sql [SQL query syntax]: inv:crate-reference:*:label#sql -[superuser]: inv:crate-reference:*:label#administration_user_management diff --git a/docs/start/query/ad-hoc.md b/docs/start/query/ad-hoc.md index ad83c11e..efc92542 100644 --- a/docs/start/query/ad-hoc.md +++ b/docs/start/query/ad-hoc.md @@ -5,13 +5,6 @@ Support highly dynamic ad-hoc querying even on large-scale, real-time datasets. ::: -:::::{grid} -:padding: 0 - -::::{grid-item} -:class: rubric-slimmer -:columns: auto 9 9 9 - :::{rubric} Introduction ::: @@ -57,35 +50,6 @@ They are unpredictable by nature—and CrateDB is designed to handle exactly tha - Avoid maintaining rigid ETL pipelines or OLAP cubes -:::: - -::::{grid-item} -:class: rubric-slim -:columns: auto 3 3 3 - -:::{rubric} Related Features -::: -- {ref}`object` -- {ref}`fts` -- {ref}`timeseries` - -:::{rubric} Reference Documentation -::: -- {ref}`CrateDB SQL Reference ` -- {ref}`CrateDB Console ` -- {ref}`crate-reference:data-types-objects` -- {ref}`crate-reference:fulltext-indices` - -:::{rubric} Learn more -::: -- [Exploratory Time Series Data Analysis] -- [Academy: Time Series Query Optimization] -- [CrateDB Scalability Benchmark: Query Throughput] -:::: - -::::: - - ## Common Query Patterns ::::{grid} 2 @@ -242,6 +206,38 @@ Learn more about how to use ad-hoc queries effectively. | Full-text & filter | Combine keyword search with structured queries | {ref}`fts`
{ref}`crate-reference:fulltext-indices` | +## Further reading + +:::::{grid} 1 3 3 3 +:margin: 4 4 0 0 +:padding: 0 +:gutter: 2 + +::::{grid-item-card} {material-outlined}`article;1.5em` Documentation +:columns: 3 +- {ref}`SQL reference ` +- {ref}`crate-reference:data-types-objects` +- {ref}`crate-reference:fulltext-indices` +:::: + +::::{grid-item-card} {material-outlined}`link;1.5em` Related +:columns: 3 +- {ref}`object` +- {ref}`fts` +- {ref}`timeseries` +- {ref}`CrateDB Console ` +:::: + +::::{grid-item-card} {material-outlined}`read_more;1.5em` Read more +:columns: 6 +- [Exploratory Time Series Data Analysis] +- [Academy: Time Series Query Optimization] +- [CrateDB Scalability Benchmark: Query Throughput] +:::: + +::::: + + [Academy: Time Series Query Optimization]: https://cratedb.com/academy/time-series/time-series-data-manipulation-and-visualization/time-series-query-optimization [CrateDB Scalability Benchmark: Query Throughput]: https://cratedb.com/blog/cratedb-scalability-benchmark-query-throughput [Exploratory Time Series Data Analysis]: https://cratedb.com/data-model/time-series/exploratory-data-analysis diff --git a/docs/start/query/aggregations.md b/docs/start/query/aggregations.md index befad2a9..6a4c6ef8 100644 --- a/docs/start/query/aggregations.md +++ b/docs/start/query/aggregations.md @@ -6,13 +6,6 @@ High-performance aggregations on massive volumes of data using SQL. ::: -:::::{grid} -:padding: 0 - -::::{grid-item} -:class: rubric-slimmer -:columns: auto 9 9 9 - :::{rubric} Introduction ::: @@ -37,34 +30,6 @@ Whether you are monitoring sensor networks, analyzing customer behavior, or powe | Aggregations on any data type | Structured, JSON, full-text, geospatial, or vector | | Smart indexing | Built-in indexing and configuration options that can boost performance | -:::: - -::::{grid-item} -:class: rubric-slim -:columns: auto 3 3 3 - -:::{rubric} Documentation -::: -- {ref}`crate-reference:aggregation` -- {ref}`performance-select` - -:::{rubric} Integrations -::: -- {ref}`grafana` -- {ref}`metabase` -- {ref}`powerbi` -- {ref}`superset` -- {ref}`tableau` - -:::{rubric} See also -::: -- {ref}`analytics` -- [Hands-on: Aggregating and Grouping Data] -- [Real-Time Analytics Primer] -:::: - -::::: - ## Supported Aggregation Functions @@ -217,5 +182,37 @@ To learn about the full set of integrations, please visit the documentation at {ref}`bi` and {ref}`visualization`. -[Hands-on: Aggregating and Grouping Data]: https://cratedb.com/academy/fundamentals/working-with-data-in-cratedb/hands-on-aggregating-and-grouping-data -[Real-Time Analytics Primer]: https://cratedb.com/real-time-analytics/definition +## Further reading + +:::::{grid} 1 3 3 3 +:margin: 4 4 0 0 +:padding: 0 +:gutter: 2 + +::::{grid-item-card} {material-outlined}`article;1.5em` Documentation +:columns: 3 +- {ref}`crate-reference:aggregation` +- {ref}`performance-select` +:::: + +::::{grid-item-card} {material-outlined}`integration_instructions;1.5em` Integrations +:columns: 3 +- {ref}`grafana` +- {ref}`metabase` +- {ref}`powerbi` +- {ref}`superset` +- {ref}`tableau` +:::: + +::::{grid-item-card} {material-outlined}`read_more;1.5em` Read more +:columns: 6 +- Learn: [Real-time analytics primer] +- Learn: [Hands-on: Aggregating and grouping data] +- Solution: {ref}`analytics` +:::: + +::::: + + +[Hands-on: Aggregating and grouping data]: https://cratedb.com/academy/fundamentals/working-with-data-in-cratedb/hands-on-aggregating-and-grouping-data +[Real-time analytics primer]: https://cratedb.com/real-time-analytics/definition diff --git a/docs/start/query/ai-integration.md b/docs/start/query/ai-integration.md index b1cc8cde..ea36bde6 100644 --- a/docs/start/query/ai-integration.md +++ b/docs/start/query/ai-integration.md @@ -1,13 +1,6 @@ (ai-integration)= # AI integration -:::::{grid} -:padding: 0 - -::::{grid-item} -:class: rubric-slimmer -:columns: auto 9 9 9 - :::{rubric} Introduction ::: @@ -33,36 +26,6 @@ Whether you're training models, running batch or real-time inference, or integra | Monitoring | Track model performance, drift, or input quality | | Data Collection | Capture telemetry, events, logs, and raw user data | -:::: - -::::{grid-item} -:class: rubric-slim -:columns: auto 3 3 3 - -:::{rubric} Related -::: -- {ref}`vector-search` -- {ref}`hybrid-search` -- {ref}`Machine Learning ` - -:::{rubric} Integrations -::: -- {ref}`langchain` -- {ref}`llamaindex` -- {ref}`mindsdb` -- {ref}`mlflow` -- {ref}`pycaret` - -:::{rubric} See also -::: -- [Blog: Vector support and KNN search] -- {ref}`Synopsis: Text-to-SQL ` -- {ref}`Tutorial: Text-to-SQL using Azure ` -- [Examples: ML] - -:::: - -::::: :::{rubric} Use cases ::: @@ -232,6 +195,39 @@ Learn more about how to combine ML features with other major features of CrateDB | Time-series support | Perfect for sensor-based training data | {ref}`timeseries` | +## Further reading + +:::::{grid} 1 3 3 3 +:margin: 4 4 0 0 +:padding: 0 +:gutter: 2 + +::::{grid-item-card} {material-outlined}`article;1.5em` Documentation +:columns: 3 +- {ref}`vector-search` +- {ref}`hybrid-search` +- {ref}`Machine Learning ` +:::: + +::::{grid-item-card} {material-outlined}`integration_instructions;1.5em` Integrations +:columns: 3 +- {ref}`langchain` +- {ref}`llamaindex` +- {ref}`mindsdb` +- {ref}`mlflow` +- {ref}`pycaret` +:::: + +::::{grid-item-card} {material-outlined}`read_more;1.5em` Read more +:columns: 6 +- [Blog: Vector support and KNN search] +- {ref}`Synopsis: Text-to-SQL ` +- {ref}`Tutorial: Text-to-SQL using Azure ` +- [Examples: ML] +:::: + +::::: + [Blog: Vector support and KNN search]: https://cratedb.com/blog/unlocking-the-power-of-vector-support-and-knn-search-in-cratedb [Examples: ML]: https://github.com/crate/cratedb-examples/tree/main/topic/machine-learning