Features
Choosing a cloud data warehouse in 2025 means weighing elasticity, price-performance and ecosystem depth. This guide ranks Snowflake, BigQuery, Databricks SQL Warehouse and seven other leaders, explaining where each shines and where it falls short so teams can match the right engine to their workloads.
The best cloud data warehouses in 2025 are Snowflake, Google BigQuery, and Databricks SQL Warehouse. Snowflake excels at elasticity and cross-cloud governance; Google BigQuery offers unrivaled serverless simplicity; Databricks SQL Warehouse is ideal for unified analytics across data-lake and warehouse workloads.
Snowflake, Google BigQuery, and Databricks SQL Warehouse top the 2025 leaderboard thanks to elastic scale, proven performance, and mature ecosystems. Rounding out the top ten are Amazon Redshift, Azure Synapse, Firebolt, ClickHouse Cloud, Teradata VantageCloud, SingleStore Helios, and IBM Db2 Warehouse on Cloud.
The list scores each platform across seven weighted criteria: feature depth (25%), price-performance (20%), ease of use (15%), integrations (15%), reliability (10%), support (10%), and community momentum (5%). Scoring relied on public benchmarks, 2025 customer case studies, pricing calculators, and analyst reports.
Snowflake leads because its cross-cloud control plane lets enterprises deploy the same warehouse on AWS, Azure, and GCP while enforcing unified governance through Snowgrid. The 2025 release of Snowpark Container Services further closed the gap between warehouse and lakehouse workloads without sacrificing the platform’s trademark simplicity.
While storage remains cheap, heavy compute consumption can surprise new adopters. Real-time ingest latency is higher than in specialized engines like ClickHouse Cloud, and advanced users still miss fine-grained knobs for low-level tuning.
BigQuery’s fully serverless model means no clusters to size or pause—Google provisions capacity on demand. The 2025 editions of BigQuery Editions and BigQuery Omni add predictable reservations and cross-cloud queries, giving customers more cost control without losing the pay-as-you-go ease.
Predicting cost can be challenging for exploration-heavy teams because on-demand scans are billed by processed bytes. Workloads with many small updates also pay a premium compared with columnar stores optimized for mutations.
Databricks SQL Warehouse layers Delta Lake ACID tables and Photon execution on object storage, delivering warehouse-grade performance on open formats. In 2025, Delta UniForm metadata and Delta Sharing v3 let users query the same tables from Spark, Trino, or even Snowflake without duplication.
Choose Databricks when you already run large AI or streaming pipelines on the Databricks Lakehouse and want BI dashboards on the same data without extra ETL.
Redshift’s 2025 RA4 instances and AQUA hardware accelerate joins and scans at lower cost than prior generations. Seamless integrations with AWS Glue, QuickSight, and Amazon S3 make Redshift compelling for all-in AWS shops.
Synapse pairs MPP SQL pools with a serverless on-demand tier so teams mix structured warehousing and ad-hoc lake queries. Tight coupling with Power BI and Azure Machine Learning simplifies end-to-end analytics inside the Microsoft stack.
Firebolt targets sub-second interactive analytics at scale. Its 2025 decoupled compute cache and sparse indexing deliver industry-leading price-performance for high-concurrency SaaS reporting workloads.
ClickHouse Cloud brings the open-source OLAP engine to a fully managed service with millisecond-level latency. In 2025 it adds tiered storage and SQL UDFs, making it viable beyond observability use cases.
VantageCloud Lake modernizes Teradata with object-store pricing, Native Object Storage, and a new consumption model in 2025, appealing to Fortune 500 migrations that need ANSI SQL compatibility and mixed workload management.
SingleStore combines row and column stores in one engine, excelling at hybrid transactional-analytical processing (HTAP). The 2025 release adds vector search for real-time AI applications.
IBM’s 2025 containerized Db2 Warehouse targets regulated industries needing FedRAMP High compliance and integrated watsonx.ai services for model lifecycle management.
Rightsize compute clusters or purchase capacity commitments to avoid runaway spend. Enable automatic workload management features such as Snowflake’s dynamic scaling or BigQuery’s autoslots. Partition and cluster heavily queried tables to curb scan costs.
Galaxy’s 2025 AI-powered SQL editor connects natively to every warehouse listed. Its context-aware copilot writes and optimizes queries, while Collections let teams endorse vetted SQL snippets—eliminating Slack copy-pasta and accelerating development on Snowflake, BigQuery, and beyond.
Snowflake tops most analyst matrices because it balances elastic scale, cross-cloud support, and an unmatched marketplace. However, workloads prioritizing serverless simplicity or lakehouse unification may prefer BigQuery or Databricks.
Purchase edition-based slot commitments, cluster heavily scanned tables, and enable materialized views. The new Budget Guardrails feature alerts you before query costs spike.
Galaxy’s desktop SQL IDE connects to Snowflake, BigQuery, Databricks, and more through native drivers. Its context-aware AI copilot writes, explains, and optimizes SQL, while Collections let teams endorse trusted queries—speeding up collaboration and reducing costly errors.
Lakehouses like Databricks shine for mixed analytics and AI pipelines on open formats. Traditional warehouses such as Snowflake excel at managed performance and governance. Many enterprises run both and query through a unified tool like Galaxy.
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