Reliable and affordable data streaming cloud service

DigitalOcean provides fast, consistent, scalable data streaming hosting so you can focus on building your streaming data application and grow your business. DigitalOcean offers easy and intuitive tools, affordable pricing, and robust support so you don’t have to worry about your infrastructure and can concentrate on delighting your customers.

DigitalOcean helps your streaming data service succeed with substantial compute

If your big data business needs to process and analyze huge amounts of data, you are going to need best-in-class computing. With DigitalOcean, you can run your data streaming jobs directly on our virtual machines, Droplets, or via our managed Kubernetes offering.

Virtual Machines

Virtual Machines

DigitalOcean offers a wide variety of virtual machine (Droplets) options to fit your needs: Basic virtual machines, General Purpose, CPU-Optimized, and Memory-Optimized. Spin up a Droplet today.

DigitalOcean Kubernetes

DigitalOcean Kubernetes

Create a managed Kubernetes cluster in seconds. Unlock the power of containerization to easily scale your app (while only paying for the worker nodes you need).

DigitalOcean gives you the building blocks for big data storage.

Storing and retrieving your data should be simple and affordable. DigitalOcean provides infrastructure and storage technology for building up and operating your big data workload.

Spaces (Object Storage)

Spaces (Object Storage)

Store your extensive data in one of our global data centers with S3-compatibility. Leverage our built-in CDN to improve your retrieval times and your ability to manipulate your data.

Volumes (Block Storage)

Volumes (Block Storage)

Our Volumes solution makes it easier for you to scale your application by providing extra highly available and resizable SSD storage when you need it.

Pick the Framework that works best for you

After you’ve spun up your infrastructure, you can deploy whatever big data framework is the best fit for you and your business. Many other DigitalOcean customers use Apache Hadoop or Apache Spark.

Apache Hadoop

Apache Hadoop

Apache Hadoop is a very popular batch processing framework used by many successful data-oriented businesses

Apache Spark

Apache Spark

Apache Spark offers both batch and stream processing with full in-memory computation and processing optimization.

Data streaming companies find success on DigitalOcean’s cloud

DigitalOcean’s cloud services have helped many companies with streaming data grow and succeed. Our flexible cloud and hosting solutions will empower you to focus on your business’s goals without worrying about your infrastructure costs and reliability.

We run a Mesos Cluster with HDFS on DigitalOcean. This cluster handles our data pipeline, model generation, databases, and end-user applications, enabling us to process over 200k requests per second.

Rick O'Toole

CTO Rockerbox

DigitalOcean’s low-cost servers made it feasible for us to offer a free trial to new customers.

Todd Persen

Co-Founder and CTO

We still use some Amazon services, but 95% of our system works with DigitalOcean nodes.

Den Golotyuk


Get started on DigitalOcean today

Let us help you build your mobile or web applications streaming data!

Frequently Asked Questions (FAQ)

What are data streams?

Streaming data or data streams refers to the stream data created by the users or customers interacting with your application–this abundance of information generated is what is referred to as data streams. This data can range from simple log files generated by users to purchase data, credit card information, sentiment analysis, sensor data, IoT, and much much more. Sometimes this data is streamed in real time, meaning that you’ll get visibility into the data your users create immediately. Cloud providers like DigitalOcean can offer this benefit. Through our compute and database services.

Does any application I build have streaming data?

Not all applications will have streaming data. Streaming data is present in most applications that have active users or customers. Handling so much streaming data from users may require improved batch processing, real time analytics, access to continuous data or historical data, up-to-date streaming data architecture, data lakes, a universal data pipeline, time series data, and many other technical considerations. Using a service like DigitalOcean to handle your streaming data infrastructure can take some of the hassle of managing your stream processing systems away.

How do I know if my application has streaming data?

It is likely your application (or you as the project or business owner) will need to process data, as you’ll want to understand how your visitors, users, customers, etc. are engaging with the technology, site, app, etc. you’ve built. Data management is important for growing a business, and so having easy data access is often top-of-mind for developers or businesses trying to scale.

How do I process raw data?

Data can come in all kinds of types or data records. You can end up collecting system logs, dynamic data, data in real time, and other data types. You’ll typically want to understand all your data sources and have data centers hold the data you collect. DigitalOcean’s products and services can help with data management and help you process data streams or a single data stream.

As far as processing raw data goes, we recommend looking into Apache Hadoop or Apache Spark.

Do I need to process streaming data to be successful?

Every business and project is different. While streaming data, batch processing, real time analytics (or at least data in real time), etc is critical for many businesses, we cannot know what the needs of your business are. Data stream processing is very common among the most successful internet-based companies, so at the very least stream processing is probably worth looking into.

Some internet-based businesses today even have data scientists on staff. Data scientists are engineers wholly dedicated to helping manage and analyze data. Many data scientists today are even skilled in cutting-edge techniques such as machine learning (and applying machine learning algorithms) or using streaming data sensors.

We actually have blog posts and tutorials that cover machine learning topics. Machine learning is an exciting new frontier in data analysis.

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