Azure Synapse Analytics alternatives

3 tools to consider instead of Azure Synapse Analytics, shown against it.

Azure Synapse Analytics Microsoft Fabric Amazon Redshift Google BigQuery
Vendor Microsoft Corporation Microsoft Corporation Amazon Web Services, Inc. Google LLC (Google Cloud)
Pricing model Usage-based Usage-based Usage-based Usage-based
Free tier No Yes Yes Yes
Deployment Cloud Cloud Cloud Cloud
Open source No No No No
Best for Azure-centric enterprises needing both provisioned data warehousing and ad hoc lake querying in one service. Microsoft-centric organizations wanting warehouse, lakehouse, and BI on one capacity and one copy of the data. AWS-centric teams wanting a managed warehouse tightly integrated with the rest of the AWS data stack. Teams already on Google Cloud who want a serverless warehouse with no cluster management.
Pricing

Dedicated SQL pools bill per DWU-hour with pay-as-you-go or 1-/3-year reserved options; serverless SQL pools bill per TB of data processed with a 10 MB minimum per query; Spark pools bill per vCore-hour.

Checked on the vendor's own page on September 21, 2026: no prices are published. Expect to be quoted.

Billed as reserved or pay-as-you-go Fabric capacity units (F2 through F8192+), shared across warehouse, lakehouse, pipeline, and Power BI workloads; a free trial capacity is offered, and 1-/3-year reservations discount the pay-as-you-go rate by roughly 41%.

Checked on the vendor's own page on September 21, 2026: no prices are published. Expect to be quoted.

Provisioned clusters are billed hourly per node type; Redshift Serverless bills per RPU-hour with a per-second minimum; new Serverless users get trial credits and provisioned clusters offer a limited free-tier trial.

RA3 provisioned (example) $3.26/hr for 4x ra3.4xlarge
Redshift Serverless $0.375 per RPU-hour
Managed storage $0.024/GB-month
New Serverless users $300 trial credit

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

On-demand queries are billed per tebibyte scanned with 1 TiB free per month; capacity pricing bills per slot-hour by edition (Standard, Enterprise, Enterprise Plus); storage is billed separately per GiB, discounted after 90 days of inactivity.

On-demand queries $6.25 per TiB
Standard edition slots $0.04 per slot-hour
Enterprise edition slots $0.06 per slot-hour
Active logical storage $0.000031507 per GiB-hour

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Features
  • Dedicated (provisioned) SQL pools measured in DWUs
  • Serverless SQL pools querying data lake files on demand
  • Native Apache Spark pools for data engineering and ML
  • Built-in Synapse Pipelines for data integration and orchestration
  • Unified Synapse Studio workspace for SQL, Spark, and pipelines
  • Deep integration with Power BI and Azure Data Lake Storage
  • Workload management and resource classes for query prioritization
  • Unified OneLake storage layer built on open Delta Lake tables
  • SQL-based Warehouse item alongside a Spark-based Lakehouse item
  • Shared F-SKU capacity across warehouse, lakehouse, and BI workloads
  • Native Power BI integration with Direct Lake mode
  • Real-Time Intelligence with KQL databases and eventstreams
  • Data Factory-style pipelines and dataflows for ingestion
  • Copilot-assisted data engineering and report authoring
  • Provisioned (RA3) or auto-scaling Serverless (RPU-based) deployment
  • Redshift Spectrum for querying S3 data lakes directly
  • Zero-ETL integrations from Aurora, RDS, and DynamoDB
  • Concurrency scaling for bursty query workloads
  • Materialized views and automatic query result caching
  • Machine learning via Redshift ML (SageMaker integration)
  • Federated querying across other AWS databases
  • Serverless architecture with automatic compute allocation
  • On-demand (per-TiB) or capacity (per-slot) pricing models
  • BigQuery ML for in-warehouse model training via SQL
  • BI Engine in-memory acceleration for dashboards
  • BigQuery Omni for federated queries over other clouds
  • Native streaming ingestion via the Storage Write API
  • Materialized views and automatic query result caching
  • Fine-grained IAM, column-level security, and row-level access policies

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