Snowflake vs Azure Synapse

Quick verdict

Snowflake is a fully managed cloud data platform that runs on AWS, Microsoft Azure and Google Cloud. Storage and compute are separate; queries run on virtual warehouses that are billed per second in credits and can suspend automatically when idle. It is sold in four editions (Standard, Enterprise, Business Critical and Virtual Private Snowflake). See Snowflake vs Databricks for its features beyond SQL warehousing.

Azure Synapse Analytics brings together several engines in one workspace: dedicated SQL pools (formerly SQL DW, a provisioned massively parallel T-SQL warehouse sized in Data Warehouse Units), serverless SQL pools (pay-per-query T-SQL over files in the data lake), Apache Spark pools, and pipelines that use the same integration engine as Azure Data Factory, all managed in Synapse Studio.

Side by side

Key differences

Microsoft's direction: Synapse, Fabric and what it means for you

Microsoft has not announced a retirement date for Azure Synapse Analytics, and its lifecycle entry shows it in support. What has changed is the guidance. The dedicated SQL pool documentation recommends Fabric Data Warehouse to anyone new to data warehousing, and Microsoft Learn has a full migration track: a planning guide, a Fabric Migration Assistant for Data Warehouse for automated migration from dedicated SQL pools, and separate guides for Synapse Spark, pipelines and Hive metastore metadata.

Moving to Fabric is not a zero-change upgrade. Microsoft's planning guide lists data type mappings: for example nvarchar becomes varchar, nchar becomes char, datetime and smalldatetime become datetime2, money becomes decimal(19,4), tinyint becomes smallint, and datetimeoffset is not supported, so time zone offsets need a separate column. Some T-SQL may need rewriting, and indexes and distribution choices are not carried over because Fabric manages those optimisations itself.

For an existing Synapse customer, the decision is therefore usually between three options: stay on Synapse for now, move to Fabric with Microsoft's tooling, or move to another platform such as Snowflake. Each move is a migration project; in our view, the type and T-SQL changes Fabric requires mean the effort gap between moving to Fabric and moving to Snowflake is smaller than a "Microsoft to Microsoft" upgrade might suggest, so it is worth costing both.

Architecture and scaling

A Synapse dedicated SQL pool has a Control node that optimises queries and Compute nodes that run them in parallel. Data is stored in Azure Storage, sharded into 60 distributions, and you choose for each table whether rows are hash-distributed on a column, spread round-robin, or replicated to every node. Service levels range from DW100c (one compute node) to DW30000c (60 compute nodes). Scaling changes the service level and remaps distributions; pausing stops compute billing while keeping the data. Concurrency is bounded by the service level: Microsoft documents a maximum of 4 concurrent queries at DW100c, rising to 128 at DW6000c and above with workload groups.

-- T-SQL (Synapse dedicated SQL pool): hash-distributed fact table
CREATE TABLE dbo.fact_sales (
    sale_id     BIGINT        NOT NULL,
    customer_id INT           NOT NULL,
    sale_date   DATE          NOT NULL,
    amount      DECIMAL(12,2) NOT NULL
)
WITH (
    DISTRIBUTION = HASH(customer_id),
    CLUSTERED COLUMNSTORE INDEX
);

-- Scale the pool (run in the master database)
ALTER DATABASE mydw MODIFY (SERVICE_OBJECTIVE = 'DW1000c');

Snowflake hides distribution entirely. You size a virtual warehouse; each size up doubles its credits per hour, and it suspends after a set idle time and resumes on the next query. For more concurrent users, Enterprise edition and above can run multi-cluster warehouses that start extra clusters when queries queue, either in auto-scale mode (with a Standard or Economy scaling policy) or maximized mode. In our view, the usual pattern of separate warehouses for loading and for reporting is simpler to run than workload groups in a single dedicated pool.

-- Snowflake: equivalent table, optional clustering key
CREATE TABLE fact_sales (
    sale_id     NUMBER(38,0) NOT NULL,
    customer_id NUMBER(38,0) NOT NULL,
    sale_date   DATE         NOT NULL,
    amount      NUMBER(12,2) NOT NULL
)
CLUSTER BY (sale_date);

-- Resize a warehouse
ALTER WAREHOUSE reporting_wh SET WAREHOUSE_SIZE = 'MEDIUM';

Billing models

Synapse bills each engine separately: dedicated SQL pools per hour at the chosen DWU level (with 1-year and 3-year reserved capacity available), plus storage per TB per month and geo-redundant backup storage; serverless SQL pools per TB of data processed, with a 10 MB minimum per query and no charge for metadata-only statements; Spark pools per vCore-hour; and pipelines by activity runs and integration runtime hours. A dedicated pool bills for every hour it is running, whether or not it is busy, unless you pause it.

Snowflake bills compute in credits only while a warehouse runs (per second, 60-second minimum per start), storage per TB per month, and data transfer out of a region or cloud. Cloud services usage is charged only above 10% of daily warehouse usage. See the pricing section for an Azure-region example.

Ecosystem and tooling on Azure

Synapse is native to Azure: Microsoft Entra authentication, Synapse Studio for SQL, Spark and pipelines in one place, Power BI workspace links, Git-based CI/CD for workspace artefacts, and database projects for dedicated pool objects. Dedicated and serverless SQL pools are reachable from SSMS; Microsoft notes that for serverless SQL pools SSMS supports connecting and querying only, and lists the mssql extension for VS Code as a supported tool.

Snowflake runs in Azure regions as well as on AWS and Google Cloud, so it can sit next to Azure data sources. Microsoft documents interoperability with Fabric in both directions: Snowflake can write Iceberg tables to OneLake and read OneLake Delta tables as Iceberg, and Fabric can mirror Snowflake databases into OneLake. SQL clients with Snowflake support include DataGrip and DBeaver.

Pricing and licensing

Snowflake. Compute is billed in credits (per second, 60-second minimum per warehouse start) and storage per TB per month, On Demand or on prepaid Capacity contracts. As one example, Snowflake's Service Consumption Table (effective 2 October 2026, USD) lists the On Demand price per credit in Azure East US 2 (Virginia) as USD 2.00 for Standard, USD 3.00 for Enterprise and USD 4.00 for Business Critical edition. A first-generation X-Small warehouse uses 1 credit per hour and each size up doubles that. Prices are higher in many other regions, and storage is priced per region in the same table. Snowflake offers a 30-day free trial.

Azure Synapse Analytics. Dedicated SQL pools are billed per hour by service level (DW100c to DW30000c), pay-as-you-go or with 1-year or 3-year reserved capacity, which the Azure pricing page says can save up to 65%; storage is billed per TB per month including 7 days of snapshots, plus geo-redundant recovery storage. Serverless SQL pools are billed per TB of data processed (10 MB minimum per query). Spark pools are billed per vCore-hour. The Azure pricing page shows figures only after choosing a region and currency, so we do not quote a price here; use the Azure pricing calculator. If you are comparing with Fabric, note that Fabric is billed as a shared F SKU capacity instead (see Databricks vs Microsoft Fabric).

Pricing checked on the vendors' official pages on 7 October 2026. Prices change; confirm before buying.

Where each one leads

Limitations

When to choose each

When neither is right

• You are starting fresh on Azure and want Microsoft's current platform: evaluate Microsoft Fabric; see Databricks vs Microsoft Fabric.
• Data engineering and machine learning matter more than SQL warehousing: see Snowflake vs Databricks.
• You are choosing between cloud-native warehouses on other clouds: see Snowflake vs BigQuery and Snowflake vs Redshift.
• Your data fits in one relational database and you need reports rather than a warehouse: see Data warehouse vs database and Azure SQL Database vs SQL Server.

Final recommendation

Frequently asked questions

Sources

• Microsoft Learn: What is Azure Synapse Analytics?
• Microsoft Learn: What is dedicated SQL pool (formerly SQL DW)?
• Microsoft Learn: Dedicated SQL pool architecture
• Microsoft Learn: Memory and concurrency limits
• Microsoft Learn: Azure Synapse Analytics FAQ
• Microsoft Lifecycle: Azure Synapse Analytics
• Microsoft Learn: Migrate from Azure Synapse Data Explorer to Fabric
• Microsoft Learn: Migration planning for Synapse dedicated SQL pools to Fabric
• Microsoft Learn: Migrating Azure Synapse Spark to Fabric
• Microsoft Learn: Connect to Synapse SQL with SSMS
• Azure Synapse Analytics pricing
• Microsoft Learn: Use Iceberg tables with OneLake
• Snowflake: Overview of editions
• Snowflake: Understanding overall cost
• Snowflake: Multi-cluster warehouses
• Snowflake Service Consumption Table (effective 2 October 2026)

Checked October 2026.

How we research comparisons: our editorial method.