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
SingleStore
Score 7.8 out of 10
N/A
SingleStore aims to enable organizations to scale from one to one million customers, handling SQL, JSON, full text and vector workloads in one unified platform.
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.
Good for Applications needing instant insights on large, streaming datasets. Applications processing continuous data streams with low latency. When a multi-cloud, high-availability database is required When NOT to Use Small-scale applications with limited budgets Projects that do not require real-time analytics or distributed scaling Teams without experience in distributed databases and HTAP architectures.
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.
It does not release a patch to have back porting; it just releases a new version and stops support; it's difficult to keep up to that pace.
Support engineers lack expertise, but they seem to be improving organically.
Lacks enterprise CDC capability: Change data capture (CDC) is a process that tracks and records changes made to data in a database and then delivers those changes to other systems in real time.
For enterprise-level backup & restore capability, we had to implement our model via Velero snapshot backup.
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.
[Until it is] supported on AWS ECS containers, I will reserve a higher rating for SingleStore. Right now it works well on EC2 and serves our current purpose, [but] would look forward to seeing SingleStore respond to our urge of feature in a shorter time period with high quality and security.
Solutions are based around a business needs and even when implementing such solution, real time insights are also followed through showing the updates the business are implementing while informing the end users as what is new with technology.
SingleStore excels in real-time analytics and low-latency transactions, making it ideal for operational analytics and mixed workloads. Snowflake shines in batch analytics and data warehousing with strong scalability for large datasets. SingleStore offers faster data ingestion and query execution for real-time use cases, while Snowflake is better for complex analytical queries on historical data.
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 support deep dives into our most complexed queries and bizarre issues that sometimes only we get comparing to other clients. Our special workload (thousands of Kafka pipelines + high concurrency of queries). The response match to the priority of the request, P1 gets immediate return call. Missing features are treated, they become a client request and being added to the roadmap after internal consideration on all client needs and priority. Bugs are patched quite fast, depends on the impact and feasible temporary workarounds. There is no issue that we haven't got a proper answer, resolution or reasoning
We allowed 2-3 months for a thorough evaluation. We saw pretty quickly that we were likely to pick SingleStore, so we ported some of our stored procedures to SingleStore in order to take a deeper look. Two SingleStore people worked closely with us to ensure that we did not have any blocking problems. It all went remarkably smoothly.
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.
Greenplum is good in handling very large amount of data. Concurrency in Greenplum was a major problem. Features available in SingleStore like Pipelines and in memory features are not available in Greenplum. Gemfire was not scaling well like SingleStore. Support of both Greenplum and Gemfire was not good. Product team did not help us much like the ones in SingleStore who helped us getting started on our first cluster very fast.
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...
As the overall performance and functionality were expanded, we are able to deliver our data much faster than before, which increases the demand for data.
Metadata is available in the platform by default, like metadata on the pipelines. Also, the information schema has lots of metadata, making it easy to load our assets to the data catalog.
