What is an AWS users list?

An AWS users list is a marketing database of companies that use Amazon Web Services, along with verified contact and company details of the decision-makers and professionals involved in managing or influencing cloud infrastructure decisions. The list consists of contact data such as emails, direct phone numbers, mailing addresses, social media profiles, and more, for targeted outreach purposes.

How accurate is your AWS users email list compared to typical B2B data providers?

Span Global Services' AWS users email list maintains a 97%+ email deliverability rate, supported by a three-step validation process: automated email verification, manual research by data specialists, and AI-based enrichment. This reduces bounce rates significantly compared to standard B2B datasets, which typically range between 75% and 85%.

How many companies using AWS are included in your database, and how are they identified?

Our database tracks 835,000+ companies using AWS, identified through technographic signals such as cloud infrastructure patterns, job postings, engineering stack references, and third-party data validation. This ensures the list reflects actual AWS adoption, not inferred or outdated records.

What response rates can be expected when targeting AWS users for outreach?

Campaigns targeting AWS users typically achieve 20% to 40% higher engagement rates compared to generic IT lists. This is because AWS adoption indicates active infrastructure investment, making these accounts or prospects more responsive to relevant cloud, SaaS, and data-driven solutions.

Can your AWS users list be segmented based on specific AWS services?

Yes. Our AWS technographic data allows segmentation by specific AWS services and infrastructure patterns, including EC2, S3, Lambda, Redshift, and Kubernetes environments.

How frequently is your AWS customer database updated?

The database is refreshed every 30 days, during which outdated or inactive records are either revalidated or removed. This continuous update cycle ensures that your campaigns are always based on current and usable data, not static records.

Do you provide AWS users list segmentation by geography?

Yes. You can request highly targeted segments, such as an AWS users list USA, or filter by country, state, or city. The database covers 30+ global markets, allowing both regional and global campaign execution.

What makes your AWS technographic data different from standard firmographic databases?

Unlike standard databases that only provide company size and industry, our AWS technographic data captures real infrastructure signals, including cloud services used, tech stack combinations, and deployment patterns. This allows for behavior-based targeting, which is more effective than static segmentation.

Can I combine AWS data with other technologies for multi-layer targeting?

Yes. Span Global Services' build custom list feature allows you to obtain lists with segments such as AWS + Salesforce, AWS + Snowflake, or AWS + Kubernetes. This multi-layer targeting approach significantly improves campaign relevance and helps align messaging with the prospect's existing environment.

How does your AWS users mailing list support ABM strategies?

Our AWS users mailing list enables ABM by allowing you to filter decision-makers based on industry, company size, AWS usage, and technology stack. This helps you focus on high-fit accounts and run personalized, high-impact campaigns for lead acquisition and conversion.

What industries show the highest concentration of AWS customers in your database?

The highest concentration of AWS customers is in technology (32%), followed by financial services (18%), e-commerce (14%), and healthcare (11%). These industries typically have higher cloud adoption rates and stronger demand for scalable infrastructure solutions.

Databricks Users List | 109K+ Verified Customer Contacts

GDPR & CAN-SPAM Compliant

96%+ Email Deliverability

Updated Every 30 Days

Free Sample Available

Why Choose Our Databricks Users Email List

Span Global Services’ Databricks customer database is built for revenue teams that need precise targeting, not bloated lists with stale records.

Every record is structured for campaign execution, helping you identify Databricks customers based on real adoption signals, deployment scope, and decision-maker authority instead of generic firmographic guesses. With 15,717 verified companies and 109,726 active decision-maker contacts, we deliver the depth and accuracy needed for enterprise-grade ABM and demand generation campaigns.

Segmentation
Filters

Technology Intelligence

Databricks Products Confirmed In-Use (Lakehouse Platform, Delta Lake, Unity Catalog, Mosaic AI, Databricks SQL, MLflow, Workflows, DLT) | Cloud Deployment (AWS, Azure, Google Cloud, Multi-Cloud) | Estimated Databricks Spend Tier | Other Technology Co-Adoptions (Data Warehouses, BI, ETL, ML platforms)

Contact Information

96% email deliverability guarantee.

Validation Accuracy

Email verification and validation accuracy rate of over 96%

Triple verification process:

Automated email syntax and domain validation,
Manual research by data specialists,
AI-powered enrichment and cross-referencing.

Bounce replacement guarantee within 30 days.

30 days

Refresh Frequency

Data is verified and refreshed every 30 days for accuracy and relevancy

Get a Custom Databricks Users List

Support

Dedicated account manager | 30-day post-delivery support | Free sample available before purchase | Custom list building on requestt

Compliance Status

Delivery Format

CSV | XLS | TXT | CRM-ready import packages for Salesforce, HubSpot, Marketo, Pardot, and Dynamics 365

Category	Adoption Rate	Key Tools
Cloud Hyperscalers	100% adoption	AWS (45%), Microsoft Azure (38%), Google Cloud (12%), Multi-cloud (5%)
Data Warehousing & Lakehouse	81% adoption	Snowflake (often co-deployed), Amazon Redshift, Google BigQuery, Delta Lake (native), Apache Iceberg
BI & Analytics	74% adoption	Power BI, Tableau, Looker, Databricks SQL (native), Sigma, ThoughtSpot
ETL & Data Integration	68% adoption	Fivetran, dbt, Apache Spark (native engine), Airflow, Informatica, Matillion
ML & AI Platforms	62% adoption	MLflow (native), Mosaic AI (native), Hugging Face, OpenAI, Anthropic, Weights & Biases
Data Governance & Catalog	47% adoption	Unity Catalog (native), Collibra, Alation, Atlan
CRM & Sales	58% adoption	Salesforce (heavy enterprise overlap), HubSpot, Microsoft Dynamics CRM
Data Streaming	41% adoption	Apache Kafka, Confluent, Amazon Kinesis, Azure Event Hubs
Observability & DataOps	39% adoption	Datadog, Monte Carlo, Acceldata, Soda
Collaboration & Workflow	78% adoption	Slack, Microsoft Teams, Jira, Notion, Confluence