What is Databricks Used For | Guide by Erathos

What is databricks used for: a complete guide

What is Databricks used for is one of the most common questions among data professionals and decision-makers trying to make sense of today’s data platforms. In this article, we go straight to the point: Databricks helps companies centralize, organize and get value from data by combining data storage, analytics, and AI tools in a single place. Here, Erathos unpacks Databricks' main use cases, why it matters for businesses, and practical examples to bring it all to life.

See more on Databricks to Hubspot.

Understanding the databricks platform

Databricks has evolved quickly from a specialized analytics environment to a foundational part of many companies’ data stacks. But what actually makes Databricks unique, especially compared with classic data storage options? Let’s get to the essence.

Core features of databricks

The Databricks platform is built around a few pillars that make daily work with data easier and more scalable:

• Unified data infrastructure: It combines data storage, analytics, and machine learning tools. This means you don’t need to keep jumping between platforms for different stages of a project.

• Collaboration: Databricks offers shared “workspaces” where both technical and business teams can work together without constant handover bottlenecks.

• Spark engine: Underneath, Databricks runs Apache Spark. That brings speed and scalability for when data volumes start to feel intimidating.

• Automation: Scheduled jobs, notebooks, and dashboards, all in one place. Automation cuts manual processes that can slow down teams.

Databricks turns complex data work into a more manageable routine.

How it differs from traditional data warehouses

Traditional data warehouses are like large, tidy filing cabinets: structured, reliable, but often a bit stiff when you need new types of analysis or want to add machine learning. Databricks is more like a digital workbench. You can store structured and semi-structured data, run experiments, and build models much more fluidly.

But there’s a catch: the flexibility can be overwhelming at first. This is where a focused platform like Erathos makes a real difference by simplifying the Extract and Load (EL) steps, turning integration into a much shorter path.

Main use cases of databricks

For many, understanding what Databricks is used for comes down to the real-world applications that matter: How does it actually support my data goals?

Data engineering and ETL pipelines

At its core, Databricks shines when building and automating the path for data to move from point A to B. Whether collecting logs from website visits, pulling customer transactions, or tracking supply chains, Databricks makes it easier to:

• Extract data from multiple sources

• Organize and load it into a central repository

• Schedule recurring jobs to keep everything up to date

For organizations that just need data pipelines, Erathos offers a direct approach that skips unnecessary complexity, focusing on moving data without advanced transformation, just what many growing businesses need.

Advanced analytics and machine learning

One of the key reasons companies add Databricks to their stack is for advanced analytics. By bringing notebooks, workflows, and AI model training into a collaborative environment, teams can:

• Test statistical models on real business data

• Work together on machine learning pipelines

• Operationalize data science projects faster

This is where Databricks starts to feel like more than just another database. Its native tools simplify experimentation, especially for mixed teams of analysts, data engineers, and business users.

Real-time data processing

Not all reporting can wait until tomorrow. Sometimes, you need data streaming and instant aggregation,like when tracking website traffic, financial ticks, or inventory counts. Databricks lets you build real-time data streams so your decision-making is always based on the freshest information.

With Erathos handling the heavy lifting of data integration, you can keep your Databricks environment current with every new data event, no matter the scale.

Business intelligence and decision-making

Ultimately, all this work comes back to a single goal: helping people make better decisions, faster. Databricks integrates easily with BI tools so dashboards, reports, and insights flow without friction.

When your dashboard updates in real time, you spot opportunities quicker.

Why companies choose databricks

After looking at the main applications, another pressing question is: Why do teams pick Databricks over other tools? Here are some common reasons, along with thoughts on when Erathos is the better fit.

Benefits for startups and enterprises

Both large companies and startups gravitate to Databricks for its blend of flexibility and power. For startups, it’s about getting quick results without building from scratch. For big enterprises, it’s about scaling analytics to match growth, bringing teams together, and keeping costs predictable.

Scalability and cloud flexibility

Databricks was built for the cloud, so growing from a side project to full production is mostly straightforward. If your needs change, compute power can scale up or down with a few clicks.

At Erathos, we see this as a clear advantage. Our platform complements Databricks by offering data movement that adapts to the cloud, on-premise, or hybrid settings, always keeping control in your hands.

Cost efficiency compared to other tools

Some platforms in the market promise similar workflows but end up requiring expensive services or steep learning curves. Databricks offers transparent pricing as you grow. While competitors like Snowflake and others might share some similarities, Databricks’ collaborative workspaces are a real standout for teams that want to build together, not just run isolated queries.

Still, if you just want to get your data into Databricks smoothly, Erathos provides an intuitive, more accessible solution, no programming required, no hidden long-term commitments.

Databricks vs hubspot integration opportunities

Integration is more than a technical challenge; it’s the gateway to better business outcomes. Let’s look at a popular scenario, connecting Databricks and HubSpot for deeper marketing insight.

Syncing marketing data with analytics

Marketing teams using HubSpot collect plenty of leads, touchpoints, and pipeline metrics. By syncing this data into Databricks, you unlock a unified view that combines marketing performance with product, support, or sales analytics. Suddenly, you’re not just guessing about ROI, you have the numbers to back it up.

Many companies chase this manually, but with Erathos it’s straightforward: schedule data extracts from HubSpot, load them in Databricks, and keep analytics always in sync, so insights never go stale.

Building a data-driven customer journey

When marketing, sales, and product data meet in one platform, the whole customer journey line becomes visible. Instead of single snapshots, you see the full story, where customers come from, what hooks them, and what happens next.

By automating the flow from HubSpot and other sources into Databricks, you can build a truly data-driven journey map, supporting smarter campaigns and better customer experiences.

Frequently asked questions

What is Databricks mainly used for?

Databricks is mostly used for unifying data storage, processing, analysis, and machine learning in a collaborative environment. Teams can combine tools for data engineering, analytics, and AI projects in one platform, speeding up both daily workflows and long-term innovation. It’s especially valuable for businesses that work with different types of data and want to turn it into actionable business intelligence.

How does Databricks help with data integration?

Databricks centralizes data from different sources by supporting a wide range of connectors and APIs. This makes it possible to bring data together, organize it, and keep it updated for reporting and analysis. With platforms like Erathos, the integration process is even smoother, extracting and loading data automatically, no technical skills required. That way, data always flows to where it can add value.

Is Databricks good for data analytics?

Yes, Databricks is designed for data analytics. Teams use it to prepare data, build visualizations, run statistical models, and collaborate on interactive reports. From simple business dashboards to full machine learning experiments, it covers a lot of ground. Its integration with BI tools also means analytics projects are more connected and less siloed than with legacy systems.

What industries use Databricks the most?

Databricks is popular across many industries, such as retail, financial services, healthcare, tech, and logistics. Companies that rely on data to make timely decisions, especially those working with customer data, inventory, or transaction records, see the greatest benefit. Startups, growth-stage companies, and global corporations all use Databricks for its flexibility.

How secure is data on Databricks?

Data on Databricks is protected with enterprise-grade security protocols, including encryption, access controls, and regular monitoring for vulnerabilities. That said, company data policies and the responsibilities of the team also play a role. By using dedicated data movement platforms like Erathos alongside Databricks, you keep control over your pipeline and can add extra auditing or alert features as needed.

Conclusion

Databricks simplifies work with data, from integration and engineering to analytics and machine learning. Its combination of storage and advanced tools makes it a core platform for businesses wanting to turn information into action. Whether your challenge is syncing systems or unlocking new insights, the real advantage often comes from how easily data flows into the platform.

The bridge between your business and meaningful insight is data that moves freely.

If you’re ready to see how Erathos can help your company implement Databricks in a smarter, more efficient way, we’re here to guide you. Contact our team today and start building a truly data-driven business with less hassle and more clarity.