BigQuery

Exabyte-scale fully managed data warehouse (formerly ODPS) optimised for batch analytics on structured and semi-structured data, with SQL, MapReduce, and Spark computation engines, columnar storage, and tight integration with DataWorks

Apache Iceberg-native bucket type for analytical workloads with fully-managed table optimisation, automatic compaction and snapshot expiration, plus first-class integration with Athena, Redshift, EMR, and Glue — launched at re:Invent 2024

Petabyte-scale columnar data warehouse with concurrency scaling, federated queries, and a serverless option for unpredictable workloads

Serverless interactive query service that runs ANSI SQL directly on S3 data lakes with per-query pricing, Apache Iceberg and Hudi table formats, and Glue catalog integration

Managed big-data platform for running Apache Spark, Hive, Presto, Flink, Trino, and HBase across EC2, EKS, and fully serverless deployments with up to 5x faster Spark runtime and Graviton price-performance

Serverless cloud-native BI service with interactive dashboards, paginated reports, ML-powered insights, and a natural-language Q&A experience embedded via generative BI, plus per-session pricing for reader-scale deployments

Unified analytics service combining data warehousing and big data processing with dedicated and serverless SQL pools, Apache Spark, Data Integration pipelines, and Power BI embedded

First-party Microsoft-co-engineered deployment of the Databricks Lakehouse with native Entra ID sign-in, private networking, serverless SQL warehouses, Unity Catalog governance, Delta Lake storage, and Azure Portal billing — the sanctioned way to run Databricks inside an Azure subscription

Managed open-source analytics clusters for Hadoop, Apache Spark, Apache Hive LLAP, Apache Kafka, and Apache HBase with enterprise security via Enterprise Security Package, autoscale, and integration with ADLS Gen2 — used mainly for migrating existing OSS big-data estates into Azure

Unified data lakehouse combining the reliability of data warehouses with the scale of data lakes, built on Delta Lake with ACID transactions, schema enforcement, and time travel

Serverless SQL analytics warehouse optimised for BI workloads, with a native query editor, dashboards, visualisations, and connectors for Tableau, Power BI, and dbt

Query external data sources (Snowflake, Redshift, BigQuery, MySQL, Postgres, SQL Server, Salesforce) directly from Unity Catalog without ingestion — governance, lineage, and ABAC apply across all sources

MPP-architected cloud data warehouse based on Huawei's openGauss kernel with PostgreSQL compatibility, standard and stream data loading, columnar and row storage, and native integration with MRS (MapReduce Service) and OBS

Fully managed big-data platform running Apache Spark, Hive, HBase, Flink, Hadoop, and Kudu clusters with autoscaling, Kerberos security, and integration with OBS for compute-storage separation

Managed business intelligence platform with self-service dashboards, data preparation, natural-language Q&A (Answers), ML-powered auto-insights, and enterprise semantic modelling — the OBIEE successor delivered as a managed service

Managed data-lakehouse stack combining Apache Spark for batch and stream processing, Iceberg table format, and integration with object-storage data lakes, targeted at sovereign-EU analytics workloads

Managed analytics platform combining ingestion, transformation, and visualisation capabilities for European-resident data analytics workloads needing EU-jurisdictional sovereignty

Serverless analytics data warehouse — Google BigQuery operating under S3NS's French sovereign boundary. Same standard SQL surface as commercial BigQuery with datasets confined to French geography, BQML for in-warehouse ML, and integration with S3NS Cloud Storage as an external source.

Real-time customer data platform unifying data across Salesforce and external systems for analytics and personalisation

Business intelligence and data visualisation platform for self-service analytics and dashboards

Cloud-native data warehouse with separation of compute and storage, supporting structured and semi-structured data

Declarative materialised tables with target lag scheduling — define a SELECT statement and Snowflake refreshes downstream tables automatically as inputs change

Managed big-data platform running Apache Spark, Hadoop, Hive, HBase, Flink, Presto, and ClickHouse with autoscaling, Kerberos authentication, integration with COS for compute-storage separation, and Jupyter notebooks for interactive analysis