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Introduction to SQL in Bigtable
In addition to its Admin and Data APIs, Bigtable supports SQL queries.
You can use SQL to query your Bigtable data in the following
ways:
For low-latency application development, GoogleSQL for
Bigtable
For batch processing and ETL, Spark SQL
To analyze data from multiple sources, BigQuery
GoogleSQL for Bigtable
GoogleSQL is a query language used by multiple Google Cloud
services, including Spanner and BigQuery. You can create
and run GoogleSQL queries in Bigtable
Studio in the Google Cloud console,
or you can run them programmatically using one of the client libraries for
Bigtable that support SQL queries. For more information, see Use
SQL with a Bigtable client
library.
GoogleSQL for Bigtable is similar to the Cassandra
query Language (CQL) in many ways, and it includes a map data type, designed to
query the Bigtable data stored in column families, columns, and
cells.
For data science use cases or other batch processing and ETL, the
Bigtable Spark connector lets you read and write
Bigtable data using Spark SQL. For more information, see
Use the Bigtable Spark connector.
BigQuery
If you want to blend data from multiple sources, including
Bigtable, and run batch, ad hoc analytics, you can create
BigQuery external tables and run SQL queries from
BigQuery. For more information, see
Query and analyze Bigtable data with BigQuery.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-09-04 UTC."],[[["\u003cp\u003eBigtable supports SQL queries through multiple methods, including GoogleSQL for low-latency applications, Spark SQL for batch processing and ETL, and BigQuery for analyzing data from multiple sources.\u003c/p\u003e\n"],["\u003cp\u003eGoogleSQL for Bigtable, which is similar to Cassandra Query Language (CQL), can be used within the Google Cloud console via Bigtable Studio, or programmatically through the Bigtable client library for Java.\u003c/p\u003e\n"],["\u003cp\u003eThe Bigtable Spark connector enables reading and writing Bigtable data with Spark SQL, beneficial for data science and batch processing needs.\u003c/p\u003e\n"],["\u003cp\u003eBigQuery can query and analyze data from Bigtable alongside other sources using external tables, facilitating batch and ad hoc analytics.\u003c/p\u003e\n"]]],[],null,["Introduction to SQL in Bigtable\n\nIn addition to its Admin and Data APIs, Bigtable supports SQL queries.\nYou can use SQL to query your Bigtable data in the following\nways:\n\n- For low-latency application development, GoogleSQL for Bigtable\n- For batch processing and ETL, Spark SQL\n- To analyze data from multiple sources, BigQuery\n\nGoogleSQL for Bigtable\n\nGoogleSQL is a query language used by multiple Google Cloud\nservices, including Spanner and BigQuery. You can create\nand run GoogleSQL queries in [Bigtable\nStudio](/bigtable/docs/manage-data-using-console) in the Google Cloud console,\nor you can run them programmatically using one of the client libraries for\nBigtable that support SQL queries. For more information, see [Use\nSQL with a Bigtable client\nlibrary](/bigtable/docs/googlesql-overview#client-libraries).\n\nGoogleSQL for Bigtable is similar to the Cassandra\nquery Language (CQL) in many ways, and it includes a map data type, designed to\nquery the Bigtable data stored in column families, columns, and\ncells.\n\nTo get started, see the [GoogleSQL for\nBigtable overview](/bigtable/docs/googlesql-overview).\n\nSpark SQL\n\nFor data science use cases or other batch processing and ETL, the\nBigtable Spark connector lets you read and write\nBigtable data using Spark SQL. For more information, see\n[Use the Bigtable Spark connector](/bigtable/docs/use-bigtable-spark-connector).\n\nBigQuery\n\nIf you want to blend data from multiple sources, including\nBigtable, and run batch, ad hoc analytics, you can create\nBigQuery external tables and run SQL queries from\nBigQuery. For more information, see\n[Query and analyze Bigtable data with BigQuery](/bigtable/docs/bigquery-analysis).\n\nWhat's next\n\n- [Learn how to run queries in the Google Cloud console without SQL.](/bigtable/docs/query-builder)\n- [Explore the GoogleSQL for Bigtable reference documentation.](/bigtable/docs/reference/sql/functions-all)\n- [Compare tables and views](/bigtable/docs/tables-and-views)"]]
