AWS alternatives: top competitors compared
Named alongside AWS
DatabricksBest forData engineering, data science, analytics and AI teams at startups and global enterprises39% of AWS answersSnowflakeBest forEnterprises that run data engineering, analytics and AI on governed enterprise data, including large and highly regulated organizations22% of AWS answersSalesforceBest forBusinesses from small companies to large enterprises wanting sales, service, marketing and commerce on one CRM platform22% of AWS answersBigQuery20% of AWS answers
Data from SlateIndex weekly runs
AWS has a visibility score of 35.7 in MLOps Platforms, #4 of 61. AI answers that name AWS most often also name these 4.
What AI answers fault AWS for
Requires strong AWS engineering or technical expertise
Raised in 4 collected answers.
Quick reference
| Alternative | Best for | Starting price | Visibility | Key differentiator |
|---|---|---|---|---|
| Databricks | Data engineering, data science, analytics and AI teams at startups and global enterprises | — | 46.2% | One open lakehouse architecture that unifies data, analytics and AI on Delta Lake and Apache Spark |
| Snowflake | Enterprises that run data engineering, analytics and AI on governed enterprise data, including large and highly regulated organizations | Contact sales | 68.6% | Agents such as CoWork and CoCo work on governed enterprise data inside Snowflake's security perimeter, reusing existing access controls and catalog context |
| Salesforce | Businesses from small companies to large enterprises wanting sales, service, marketing and commerce on one CRM platform | — | 46.2% | One unified platform combining CRM apps, data, and AI agents |
| BigQuery | — | — | 63.6% | Serverless architecture with nothing to size, and storage and compute separated, which reviewers cite as a cost and scale advantage. |
Alternative 1
Databricks vs AWS →Databricks
Databricks suits data engineering, data science, analytics and AI teams at startups and global enterprises.
Quick facts
- Pricing not available
- 46.2% visibility score · #2 in MLOps Platforms
Key features
- Lakebase — Serverless Postgres database integrated with the lakehouse for transactional applications.
- Genie — Conversational analytics interface for natural-language questions and insights.
- Unity Gateway — Governance, cost control, observability and guardrails for enterprise AI access.
- Lakehouse — Serverless data warehousing on open lake data, with governance and AI built in.
Databricks vs AWS
| Dimension | Databricks | AWS |
|---|---|---|
| Visibility score | 46.2% | 35.7% |
| Pricing model | — | — |
| Entry price | — | — |
| Free plan | — | — |
| Trial | — | — |
Pros
- Lakehouse architecture combining data warehousing with data lake flexibility
- Strong for machine learning, AI, and data engineering workloads
- Top customer satisfaction ratings alongside Snowflake
- Free trial and free Edition for learning
- Discounts for annual prepaid commitments
Cons
- Complex consumption-based pricing with no single fixed price
- Best only when ML, Spark, or Python skills are central to the team
Alternative 2
Snowflake vs AWS →Snowflake
Snowflake suits enterprises that run data engineering, analytics and AI on governed enterprise data, including large and highly regulated organizations.
Quick facts
- Contact sales · usage-based
- 68.6% visibility score · #1 in Data Warehouse
Key features
- Snowflake CoWork — Enterprise agent for knowledge workers, formerly Snowflake Intelligence, for analysis, automation and action on governed data.
- Snowflake CoCo — Governed AI coding agent for building data pipelines, analytics, ML models, apps and agents.
- Cortex AI — Services for securely creating and deploying LLMs and ML models customized with your data.
- Openflow — Managed data integration service built on Apache NiFi.
Snowflake vs AWS
| Dimension | Snowflake | AWS |
|---|---|---|
| Visibility score | 68.6% | 35.7% |
| Pricing model | Usage-based | — |
| Entry price | Contact sales | — |
| Free plan | No | — |
| Trial | — | — |
Pros
- Multi-cloud deployment and secure, governed data sharing
- Decoupled storage and compute architecture
- Free trial with usage credits for easy getting started
- Widely adopted, most popular cloud data warehouse
- Strong for enterprise governance, high concurrency and workload isolation
Cons
- Unoptimized queries can rack up a surprisingly high bill
- Consumption pricing and credit usage are hard to predict
Alternative 3
Salesforce vs AWS →Salesforce
Salesforce suits businesses from small companies to large enterprises wanting sales, service, marketing and commerce on one CRM platform.
Quick facts
- Pricing not available
- 46.2% visibility score · #1 in Field Service Management
Key features
- Agentforce — Platform for building, deploying and running AI agents for customers and employees.
- Sales Cloud — Sales pipeline, forecasting and sales process management.
- Service Cloud — Customer support case management across channels.
- Marketing Cloud — Building and personalizing campaigns and customer journeys.
Salesforce vs AWS
| Dimension | Salesforce | AWS |
|---|---|---|
| Visibility score | 46.2% | 35.7% |
| Pricing model | — | — |
| Entry price | — | — |
| Free plan | — | — |
| Trial | — | — |
Pros
- Powerful reporting, automation and customisation
- Market leader and gold standard CRM
- Deep ecosystem and strong CRM integrations
- Built for large enterprises and scaling
- Free trial to test its features
Cons
- Requires a dedicated administrator to manage
- High enterprise pricing
- Heavy, slow implementation that suits large budgets
Alternative 4
BigQuery vs AWS →BigQuery
BigQuery is ranked #2 in Data Warehouse.
Quick facts
- Pricing not available
- 63.6% visibility score · #2 in Data Warehouse
Key features
- BigQuery AI — Lets users train, evaluate and deploy predictive models with SQL.
- BigQuery Graph — Graph-style relationship analysis.
- BigQuery Migration Service — Moves workloads from legacy warehouses to BigQuery.
- BigQuery DataFrames — A Python API for BigQuery.
BigQuery vs AWS
| Dimension | BigQuery | AWS |
|---|---|---|
| Visibility score | 63.6% | 35.7% |
| Pricing model | — | — |
| Entry price | — | — |
| Free plan | — | — |
| Trial | — | — |
Pros
- Serverless, highly scalable data warehouse
- Free tier suited to small teams and light workloads
- Easy to start with low operational overhead
- Built-in ML and AI capabilities
- Strong fit for Google Cloud-centric teams
Cons
- Bills are hard to predict
How to choose
Match the pricing model to your cost driver: headcount, usage or features.
| Platform | Pricing model | Starting price |
|---|---|---|
| AWS | — | — |
| Databricks | — | — |
| Snowflake | Usage-based | Contact sales |
| Salesforce | — | — |
| BigQuery | — | — |
More alternatives
Ranked by how often AI answers name them alongside AWS in the latest weekly run.