9 Best Cloud Data Warehouses of 2026

1. 1

   Snowflake

   A fully managed data warehouse billed per credit for compute and per terabyte for compressed storage.

   8.9overall

   A fully managed data warehouse billed per credit for compute and per terabyte for compressed storage.

   Best forData teams that want a dedicated warehouse with elastic compute and the largest disclosed warehouse revenue base.

   Adoption data

   $1.49 billionSnowflake reported product revenue of $1.49 billion for the quarter ended July 31, 2026, up 37% from a year earlier.

   Snowflake, Snowflake Reports Financial Results for the Second Quarter of Fiscal 2027 (Form 8-K, Exhibit 99.1) (2026): “Product revenue of $1.49 billion in the second quarter, representing 37% year-over-year growth”

   Snowflake is the reference cloud data warehouse for teams that want a dedicated, fully managed service separate from their lakehouse or cloud provider tooling. Its filings give the clearest adoption picture in this category: product revenue reached $1.49 billion in the quarter ended July 31, 2026, up 37 percent, with 828 customers spending more than $1 million over the trailing 12 months and 829 Forbes Global 2000 customers. Net revenue retention was 126 percent. Pricing is published per credit, at $2.00 for Standard, $3.00 for Enterprise and $4.00 for Business Critical in AWS US East, and storage costs $23 per TB per month on demand. Enterprise adds 90-day data recovery, data access rules and extra compute for busy periods, while Business Critical adds private connectivity, customer-managed keys and HIPAA, PCI DSS and FedRAMP support. The trade-off is forecasting: compute is billed by credits consumed, so cost control depends on sizing warehouses and suspending idle ones. We compared documented features and published prices rather than running benchmarks.

   Strengths

   • +Largest disclosed product revenue of any dedicated warehouse vendor in this list
   • +Clear per-credit list prices by edition and region
   • +828 customers each spent more than $1 million on the product over 12 months

   Limitations

   • −Credit consumption depends on warehouse size and run time, so bills take modeling
   • −Security and recovery features sit in higher editions at $3 and $4 per credit
   • −No permanent free plan

   SummarySnowflake is the safest default for a dedicated managed warehouse with disclosed scale. Budget owners should model credit burn per workload before committing.

2. 2

   Databricks SQL

   The SQL warehouse service of the Databricks lakehouse platform, priced per Databricks Unit (DBU).

   8.8overall

   The SQL warehouse service of the Databricks lakehouse platform, priced per Databricks Unit (DBU).

   Best forTeams that already run Spark, ML or ETL on Databricks and want BI and SQL on the same open table formats.

   Adoption data

   $5.4 billionDatabricks said it passed a $5.4 billion revenue run rate in its fiscal fourth quarter, growing more than 65% year over year, across its whole platform.

   Databricks, Databricks Grows >65% YoY, Surpasses $5.4 Billion Revenue Run-Rate, Doubles Down on Lakebase and Genie (2026): “Surpassing $5.4 billion revenue run-rate, growing >65% year-over-year.”

   Databricks SQL puts a serverless SQL warehouse on top of the Databricks lakehouse, so BI queries, ETL and machine learning share one copy of data in open table formats. Databricks does not break out SQL revenue, but the platform passed a $5.4 billion revenue run rate in early 2026, growing more than 65 percent, with more than 800 customers consuming at over $1 million a year and net retention above 140 percent. The pricing page lists three tiers: SQL Classic at $0.22 per DBU, SQL Pro at $0.55 per DBU and SQL Serverless at $0.70 per DBU, the last including cloud instance cost. Classic and Pro are self-managed warehouses whose prices exclude cloud instance cost, so the virtual machine bill comes on top. Features include the Photon engine, predictive optimization, Unity Catalog governance, Lakehouse Federation for querying outside systems and AI/BI for natural language questions. The weak spot is cost comparison, because DBUs do not map neatly to the per-credit or per-TiB rates other vendors publish.

   Strengths

   • +One platform for SQL, ETL, data science and ML
   • +Lowest published entry rate per DBU of the three SQL tiers at $0.22
   • +Open formats keep data portable

   Limitations

   • −Revenue figures cover the whole Databricks platform, not SQL alone
   • −Classic and Pro tiers add separate cloud instance bills
   • −DBU pricing is harder to compare with per-TiB or per-credit rivals

   SummaryDatabricks SQL is the strongest pick when your engineers already build pipelines and models on Databricks. Pure BI teams with no lakehouse plans may find a dedicated warehouse simpler.

3. 3

   Google BigQuery

   Google Cloud's serverless data warehouse, billed per TiB scanned or per slot-hour of reserved capacity.

   8.8overall

   Google Cloud's serverless data warehouse, billed per TiB scanned or per slot-hour of reserved capacity.

   Best forTeams that want a warehouse with no clusters to size and a free monthly query allowance to start.

   Adoption data

   $30.7 billionAlphabet reported Google Cloud revenue of $30.7 billion in the third quarter of 2026, up 103%; Google does not report BigQuery revenue separately.

   Alphabet, Alphabet Announces Third Quarter 2026 Results (Form 8-K, Exhibit 99.1) (2026): “Google Cloud delivered record growth as revenues increased 103% to $30.7 billion”

   BigQuery is the most hands-off warehouse in this list: there is nothing to provision on the default on-demand model, where you pay $6.25 per TiB of data your queries scan after a free first TiB each month. The first 10 GiB of active logical storage are also free monthly, which makes it the easiest place to start a small analytics project at no cost. Larger teams can switch to capacity pricing, buying slots by the hour in Standard, Enterprise or Enterprise Plus editions with a 50-slot minimum. BigQuery ML lets analysts train and run models in SQL, and the Storage Read API includes 300 TiB of free reads per billing account each month. Google does not disclose BigQuery revenue or customer counts, so adoption here rests on Google Cloud as a whole, which grew revenue 103 percent to $30.7 billion in the third quarter of 2026. The main risk is cost from careless scans: partition and cluster large tables before opening them to BI tools.

   Strengths

   • +Permanent free tier for queries and storage
   • +No clusters or warehouses to size on on-demand pricing
   • +Two pricing models let teams move from per-query to reserved capacity

   Limitations

   • −Per-TiB billing punishes unpartitioned full-table scans
   • −Adoption figure covers all of Google Cloud, not BigQuery alone
   • −On-demand projects share up to 2,000 concurrent slots

   SummaryBigQuery is the best way to start warehousing for free and scale without managing clusters. Teams with heavy, unpredictable ad hoc scanning should move to slot reservations early.

4. 4

   Microsoft Fabric

   Microsoft's unified analytics platform, with a data warehouse, lakehouse, Spark and Power BI on shared capacity and OneLake storage.

   8.4overall

   Microsoft's unified analytics platform, with a data warehouse, lakehouse, Spark and Power BI on shared capacity and OneLake storage.

   Best forOrganizations standardized on Azure and Power BI that want warehousing and reporting under one capacity bill.

   Adoption data

   44,000Microsoft said it had more than 44,000 paid Fabric customers, up more than 50% year over year, on its fiscal 2027 first quarter earnings call.

   Microsoft, Earnings Release FY27 Q1 (2026): “We now have over 44,000 paid Fabric customers, up more than 50 percent year over year.”

   Microsoft Fabric bundles a SQL data warehouse with lakehouse, Spark, real-time analytics and Power BI, all drawing on one pool of capacity units and one OneLake storage layer. Microsoft disclosed on its October 2026 earnings call that Fabric has more than 44,000 paid customers, up more than 50 percent year over year, which is one of the few product-level adoption figures in this category. Pricing on the Azure page starts with the F2 SKU at $262.80 per month pay as you go, or $156.334 per month reserved, and climbs through F4, F8 and up to F8192. Each capacity also includes free Mirroring storage for replicas, sized to the SKU, so an F64 includes 64 TB. The model suits Microsoft shops: if you already pay for Power BI and Azure, one capacity can replace several services. The downside is that capacity bills accrue while the capacity runs, and teams that only need a warehouse may pay for workloads they never use.

   Strengths

   • +Directly disclosed paid customer count of more than 44,000
   • +One capacity covers warehousing, Spark and Power BI
   • +Reservations cut the F2 price from $262.80 to $156.334 per month

   Limitations

   • −Capacity is billed while running, so idle time costs money unless paused
   • −Prices on the Azure page depend on region and currency settings
   • −Best value assumes you also use Power BI and other Fabric workloads

   SummaryFabric is the natural warehouse for Azure and Power BI customers who want one bill. Teams outside the Microsoft stack get less from its bundled design.

5. 5

   Amazon Redshift

   AWS's managed data warehouse, available as provisioned clusters or as Redshift Serverless billed in RPU-hours.

   8.3overall

   AWS's managed data warehouse, available as provisioned clusters or as Redshift Serverless billed in RPU-hours.

   Best forAWS-native teams that want a warehouse inside their existing account, network and IAM setup.

   Adoption data

   $46.0 billionAmazon reported AWS segment sales of $46.0 billion in the third quarter of 2026, up 39%; Amazon does not report Redshift revenue separately.

   Amazon, Amazon.com Announces Third Quarter Results (2026): “AWS segment sales increased 39% year-over-year to $46.0 billion.”

   Redshift is the warehouse most AWS-centric teams evaluate first because it lives in the same account, VPC and IAM policies as the rest of their stack. AWS lists two deployment options: provisioned clusters from $0.543 per hour and Redshift Serverless from $1.50 per hour. Serverless measures capacity in Redshift Processing Units, each with 16 GB of memory, adjustable from 4 to 1024 RPUs and billed per second with a 60-second minimum; concurrency scaling and Spectrum queries on S3 are included. Provisioned RG and RA3 nodes pair compute with managed storage that grows separately. First-time Serverless users get a $300 credit that expires after 90 days. Amazon does not publish Redshift revenue or customer counts, so adoption here reflects AWS as a whole, which grew segment sales 39 percent to $46.0 billion in the third quarter of 2026. The trade-off is choice overhead: node families, Serverless bases and reservations each change the bill.

   Strengths

   • +Runs inside your AWS account and IAM model
   • +$300 Serverless credit valid for 90 days
   • +Optional AI-driven price-performance target on Serverless

   Limitations

   • −Adoption figure covers all of AWS, not Redshift alone
   • −Choosing between node types and Serverless adds planning work
   • −Serverless entry rate of $1.50 per hour is higher than the provisioned entry

   SummaryRedshift is the practical choice when data, pipelines and security already live in AWS. Teams on other clouds or several clouds will find Snowflake or BigQuery easier to adopt.

6. 6

   ClickHouse Cloud

   The managed service for the open-source ClickHouse columnar database, with compute and storage metered separately.

   8.3overall

   The managed service for the open-source ClickHouse columnar database, with compute and storage metered separately.

   Best forEngineering teams building real-time, customer-facing analytics on large event and log tables.

   Adoption data

   3,000ClickHouse said in January 2026 that more than 3,000 customers use its managed ClickHouse Cloud service, with ARR growing more than 250% year over year.

   ClickHouse, ClickHouse raises $400M Series D, acquires Langfuse, launches Postgres (2026): “The company now serves more than 3,000 customers on its fully managed service, ClickHouse Cloud, with ARR growing more than 250 percent year over year.”

   ClickHouse Cloud is the managed version of the open-source ClickHouse database, which is built for fast aggregation over very large event, log and metrics tables. The company said in January 2026 that more than 3,000 customers use the managed service, with ARR growing more than 250 percent year over year. Pricing is metered: in AWS us-east-1, Basic compute costs $0.2181 per unit per hour and storage $25.30 per TB per month, while the Scale tier charges $0.2985 per unit per hour and adds unlimited storage, compute-compute separation, private networking and two or more availability zones. Enterprise adds SAML single sign-on and private regions. Services scale to zero when idle, and new accounts get a 30-day trial with $300 of credits. ClickHouse suits product teams that serve analytics inside an application more than BI groups that want a full governance suite. Basic's 1 TB storage cap and single availability zone also make it a starter tier only.

   Strengths

   • +Lowest published compute rate per hour in this list at $0.2181
   • +Open-source engine reduces lock-in
   • +Idle services stop billing for compute

   Limitations

   • −Basic tier limits storage to 1 TB and runs in one availability zone
   • −Storage at $25.30 per TB is above Snowflake's $23
   • −Fewer built-in BI and governance features than the largest platforms

   SummaryClickHouse Cloud is the value pick for real-time and user-facing analytics at scale. Enterprise BI teams will want to check governance and SQL compatibility first.

7. 7

   Oracle Autonomous AI Lakehouse

   Oracle's self-managing analytics database on Oracle Cloud Infrastructure, billed by ECPU per hour.

   7.8overall

   Oracle's self-managing analytics database on Oracle Cloud Infrastructure, billed by ECPU per hour.

   Best forOracle Database shops that want a managed analytics warehouse with the same SQL and tooling.

   Adoption data

   $7.4 billionOracle reported cloud infrastructure revenue of $7.4 billion in its fiscal 2027 first quarter, up 121%; Oracle does not report Autonomous Database revenue separately.

   Oracle, Oracle Announces Fiscal Year 2027 First Quarter Financial Results (Form 8-K, Exhibit 99.1) (2026): “Q1 Cloud Infra (IaaS) Revenue up 121% in USD & up 120% in constant currency to $7.4 billion.”

   Oracle's Autonomous AI Lakehouse is the analytics workload of Autonomous Database, a managed service that runs serverless on Oracle Cloud Infrastructure or on Dedicated Exadata Infrastructure. Oracle's US price list shows compute at $0.336 per ECPU per hour with the license included, or $0.0807 per ECPU per hour if you bring your own license, which makes it far cheaper for companies that already own Oracle Database licenses. A fixed-shape Developer instance with 4 ECPUs and 20 GB of storage costs $0.0391 per hour, and Elastic Pools can consolidate databases for up to 87 percent compute savings. Oracle does not report Autonomous Database revenue, so the adoption figure here is Oracle Cloud Infrastructure as a whole, which grew 121 percent to $7.4 billion in the quarter ended August 2026. The service makes most sense for existing Oracle estates; teams starting fresh will find a larger ecosystem of connectors and guides around Snowflake, Databricks or BigQuery.

   Strengths

   • +BYOL rate cuts compute cost sharply for existing Oracle licensees
   • +Low-cost Developer instance for testing
   • +Same deployment can run in Oracle Cloud or on dedicated Exadata

   Limitations

   • −Adoption figure covers all of Oracle Cloud Infrastructure
   • −Pricing mixes compute, storage and deployment metrics
   • −Smaller third-party tooling community than Snowflake or BigQuery

   SummaryOracle's lakehouse is the obvious warehouse for teams that already run Oracle Database and own licenses. Others should compare total cost and tooling support against the market leaders.

8. 8

   Teradata

   An enterprise analytics database offered as Teradata Cloud, customer-managed cloud or on premises, priced in Teradata Units.

   7.5overall

   An enterprise analytics database offered as Teradata Cloud, customer-managed cloud or on premises, priced in Teradata Units.

   Best forLarge enterprises with existing Teradata estates that need cloud, hybrid or on-premises deployment under one contract.

   Adoption data

   $700 millionTeradata reported public cloud annual recurring revenue of $700 million at the end of the third quarter of 2026, up 11%, within total ARR of $1.512 billion.

   Teradata, Teradata Reports Third Quarter 2026 Financial Results (Form 8-K, Exhibit 99.1) (2026): “Public cloud ARR increased to $700 million from $633 million, an increase of 11% as reported and 11% in constant currency”

   Teradata is the long-established enterprise warehouse in this list, and its filings show a business moving to the cloud: public cloud ARR reached $700 million at the end of September 2026, up 11 percent, out of total ARR of $1.512 billion, which grew 1 percent. The company sells one platform across Teradata Cloud, customer-managed cloud and on-premises deployments, which matters for organizations with data sovereignty requirements, regulated industries and air-gapped environments. Pricing uses a single Teradata Unit covering compute, storage, software and AI, sold as Fixed + Flex: committed capacity for steady workloads plus on-demand capacity for peaks and AI agents. Packages can be upgraded at any time, but downgrades wait until renewal. There is no public per-unit list price, so we could not verify a USD figure and scored value conservatively. Teradata makes most sense for organizations already running it at scale; new teams will find faster self-service starts elsewhere.

   Strengths

   • +Public cloud ARR disclosed in SEC filings, $700 million
   • +Same platform across cloud, customer cloud and on premises
   • +Fixed capacity gives finance teams a predictable baseline

   Limitations

   • −No public list price; quotes come from sales
   • −Total ARR grew only 1% year over year
   • −Downgrades only take effect at contract renewal

   SummaryTeradata fits large regulated enterprises that need hybrid deployment and already know the platform. Smaller teams should look at self-service warehouses with published prices.

9. 9

   MotherDuck

   A cloud data warehouse built on DuckDB, with a free Lite plan and per-organization Business pricing plus usage.

   7.2overall

   A cloud data warehouse built on DuckDB, with a free Lite plan and per-organization Business pricing plus usage.

   Best forSmall data teams, founders and developers who want a low-cost warehouse with a free tier.

   MotherDuck runs DuckDB, the in-process analytical database, as a managed cloud warehouse, so analysts can query the same data from a laptop and from the cloud. It is the cheapest way into a warehouse in this list. The Lite plan costs nothing and includes 10 GB of storage, 10 hours of Pulse compute per month, up to three internal users and two service accounts. The Business plan costs $250 per organization per month plus usage and adds up to 10 internal users, unlimited service accounts, five instance types and read-scaling replicas; storage is $0.043 per GB per month on both plans. Teams can buy directly or through AWS Marketplace. MotherDuck does not publish customer counts or revenue, so we scored adoption conservatively. It is a strong fit for startups and small data teams with gigabytes to low terabytes of data, but it lacks the enterprise governance and scale track record of Snowflake, Databricks or BigQuery.

   Strengths

   • +Permanent free plan
   • +Storage at $0.043 per GB per month
   • +Built on DuckDB, so local and cloud queries use the same engine

   Limitations

   • −No disclosed customer or revenue figures
   • −Business plan caps internal users at 10
   • −Fewer enterprise governance features than larger platforms

   SummaryMotherDuck is the best low-cost warehouse for small teams and DuckDB users. Larger organizations should confirm scale and governance needs before standardizing on it.

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