Databricks offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service provides a platform for data pipelines, data lakes, and data platforms.
$0.07
Per DBU
DigitalOcean
Score 8.6 out of 10
N/A
DigitalOcean is an infrastructure-as-a-service (IaaS) platform from the company of the same name headquartered in New York. It is known for its support of managed Kubernetes clusters and “droplets” feature.
$5
Starting Price Per Month
Pricing
Databricks Data Intelligence Platform
DigitalOcean
Editions & Modules
Standard
$0.07
Per DBU
Premium
$0.10
Per DBU
Enterprise
$0.13
Per DBU
1GB-16GB
$5.00
Starting Price Per Month
8GB-160GB
$60.00
Starting Price Per Month
Offerings
Pricing Offerings
Databricks Data Intelligence Platform
DigitalOcean
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
—
More Pricing Information
Community Pulse
Databricks Data Intelligence Platform
DigitalOcean
Features
Databricks Data Intelligence Platform
DigitalOcean
Infrastructure-as-a-Service (IaaS)
Comparison of Infrastructure-as-a-Service (IaaS) features of Product A and Product B
Medium to Large data throughput shops will benefit the most from Databricks Spark processing. Smaller use cases may find the barrier to entry a bit too high for casual use cases. Some of the overhead to kicking off a Spark compute job can actually lead to your workloads taking longer, but past a certain point the performance returns cannot be beat.
DigitalOcean is perfect for hosting client websites, running marketing tools, and managing media storage with Spaces and CDN. The use of Droplets to quickly launch landing pages or WordPress sites for campaigns is a Godsend. It’s great for fast, cheap, and scalable solutions. But for complex microservices or projects needing strict compliance (like HIPAA), DigitalOcean may not always be the best fit, but that depends heavily on your project.
Some products/services available on other Cloud providers aren't available, but they seem to be catching up as they add new products like Managed SQL DBs.
While they have FreeBSD droplets (VMs), support for *BSD OSs is limited. I.e. the new monitoring agent only works on Linux.
There are no regions available on South America.
They don't seem to offer enterprise-level products, even basic ones as Windows Server, MS SQL Server, Oracle products, etc.
Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.
in terms of graph generation and interaction it could improve their UI and UX
I honestly can't think of an easier way to set up and maintain your own server. Being able to set up a server in minutes and have fully control is awesome. The UX is incredibly intuitive for first-time users as well so there's no reason to be intimidated when it comes to giving DigitalOcean a shot.
One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.
They have always been fast, and the process has been straight-forward. I haven't had to use it enough to be frustrated with it, to be honest, and when I have an issue they fix it. As with all support, I wish it felt more human, but they are doing aces.
The most important differentiating factor for Databricks Lakehouse Platform from these other platforms is support for ACID transactions and the time travel feature. Also, native integration with managed MLflow is a plus. EMR, Cloudera, and Hortonworks are not as optimized when it comes to Spark Job Execution. Other platforms need to be self-managed, which is another huge hassle.
DigitalOcean is an inexpensive product as compared to other products available in the market. The UI is easy and the beginner can also understand the UI with the step by step guide. It provides a lot of custom features and the user needs to pay only for what they are using. Amazon has a complex UI and is on the expensive side. DigitalOcean is simple to use and is easily manageable and the servers can easily be set up without additional cost and such.
Positive - Elastic computer instances make it possible to pay for only for what you need.
Positive - Competitive pricing - some of the products that DigitalOcean offers are much cheaper than those offered by competitors.
Negative - Having to go to other cloud computing platforms for more specific, advanced services like Computer Vision optimized services, GPU cloud compute instances, etc...