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Cloud Data Warehouses

A curated index of 25 cloud data warehouse platforms — hyperscaler services, independent lakehouse and enterprise platforms, and real-time engines for analytics, BI and AI at scale.

25 platforms•3 categories•Updated October 2026

Hyperscaler & Cloud-Provider Warehouses

8 entries

Warehouses operated by the major public clouds, tightly integrated with their storage, identity and AI services.

01Amazon RedshiftAWS petabyte-scale cloud data warehouse, with serverless and provisioned options and zero-ETL integrations with other AWS data services.→ 02Google BigQueryServerless, AI-ready data platform for analytics at scale, with built-in machine learning and support for open table formats.→ 03Microsoft Fabric Data WarehouseSaaS, lake-centric T-SQL warehouse inside Microsoft Fabric, storing data in open Delta Parquet format on OneLake.→ 04Azure Synapse AnalyticsUnified analytics service that brings together enterprise data warehousing, big data processing and data integration.→ 05Oracle Autonomous Data WarehouseSelf-driving Oracle database for analytic workloads, covering data marts, warehouses, data lakes and lakehouses.→ 06IBM Db2 WarehouseCloud data warehouse for operational analytics, BI and AI workloads, with enterprise-grade security and hybrid deployment.→ 07Alibaba Cloud AnalyticDBReal-time, cloud-native data warehouse from Alibaba Cloud for high-concurrency analytics and lakehouse workloads.→ 08Huawei Cloud GaussDB(DWS)Enterprise-class, massively parallel data warehouse service from Huawei Cloud for large-scale analytics.→

Independent Cloud-Native & Lakehouse Platforms

12 entries

Vendor platforms that run across clouds or on dedicated infrastructure, from cloud-native warehouses to lakehouses and enterprise analytics suites.

09SnowflakeMulti-cloud data platform separating storage from compute, with Cortex AI services for analysing data and building AI applications.→ 10Databricks SQLData warehousing on the Databricks lakehouse, with serverless SQL compute and AI-assisted optimization over open data formats.→ 11Teradata VantageCloudEnterprise analytics platform for large, complex workloads across AWS, Azure and Google Cloud, with hybrid deployment options.→ 12SAP DatasphereBusiness data fabric that unifies SAP and non-SAP data while preserving business context for analytics and planning.→ 13Cloudera Data WarehouseSelf-service, cloud-native warehousing on an open lakehouse, deployable in public cloud and on-premises.→ 14DremioOpen lakehouse platform that runs SQL directly on data in cloud object storage, built on Apache Iceberg.→ 15FireboltCloud data warehouse designed for high-concurrency, low-latency analytics on large datasets.→ 16YellowbrickData warehouse for hybrid and multi-cloud environments that runs consistently across public clouds and on-premises.→ 17VerticaUnified analytics warehouse for in-database machine learning and large-scale analytics, on-premises or in the cloud.→ 18ExasolIn-memory, massively parallel analytics database available as a managed cloud service and for self-managed deployment.→ 19Qlik Data Warehouse AutomationAutomates the design, build and change management of data warehouses and data marts on leading cloud platforms (includes former Talend capabilities).→ 20Data Lakehouse PlatformsDirectory of lakehouse platforms and the open table formats, catalogs and engines (Iceberg, Delta Lake, Hudi) that combine warehouse and data lake capabilities.

Real-Time, Open-Source & Embedded Analytics

6 entries

Engines and managed services built for sub-second queries, high concurrency and customer-facing analytics, many with open-source cores.

21ClickHouse CloudManaged cloud service for the open-source ClickHouse column-oriented database, built for real-time analytical queries.→ 22SingleStoreDistributed SQL database that combines transactions and real-time analytics in a single platform.→ 23StarRocksOpen-source, high-performance analytical database for real-time and lakehouse queries.→ 24VeloDB (Apache Doris)Managed cloud service and enterprise offering built on Apache Doris for real-time analytics and log search.→ 25MotherDuckServerless cloud data warehouse built on DuckDB, spanning local development to cloud-scale analytics.→ 26StarTree (Apache Pinot)Real-time analytics platform built on Apache Pinot for user-facing, high-concurrency queries.→

Frequently Asked Questions

What is a cloud data warehouse?

A cloud data warehouse is a managed analytical database that runs in the cloud and is designed to store large volumes of structured and semi-structured data and answer complex SQL queries quickly. The provider operates the infrastructure, so teams can scale capacity up or down and pay for what they use instead of buying hardware.

How is a data warehouse different from a data lake or a lakehouse?

A data warehouse stores curated, structured data optimized for SQL analytics and reporting. A data lake stores raw data of any type, usually in object storage. A lakehouse combines both: it keeps data in open table formats on low-cost storage and adds warehouse features such as transactions, schemas and fast SQL. Many platforms in this list, including Databricks SQL, Dremio and Microsoft Fabric, follow the lakehouse model.

What does separating storage from compute mean?

In a separated architecture, data is stored independently of the compute clusters that query it. You can add or pause compute without moving data, run several workloads against the same data, and scale each layer on its own. Snowflake, BigQuery, Redshift and Databricks SQL all use variations of this design.

How do I choose a cloud data warehouse?

Start with where your data and workloads already live, since staying within one cloud lowers data-transfer cost and complexity. Then compare pricing models, concurrency needs, latency targets, support for open table formats, security and governance features, and integration with your BI, ETL and machine learning tools. Run a proof of concept on a representative workload before committing.

Which platforms suit real-time or customer-facing analytics?

Engines built for low-latency, high-concurrency queries, such as ClickHouse Cloud, StarRocks, Apache Doris (VeloDB), Apache Pinot (StarTree), SingleStore and Firebolt, are commonly used for dashboards and analytics embedded in applications. General-purpose warehouses such as Snowflake, BigQuery and Redshift also serve interactive analytics and are often the better fit for broad enterprise reporting.