Google Cloud AI provides modern machine learning services, with pre-trained models and a service to generate tailored models.
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IBM Cloud Object Storage
Score 9.3 out of 10
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IBM Cloud Object Storage is an IBM Cloud product in the endpoint backup and IaaS categories. It is commonly used for data archiving and backup, for web and mobile applications, and as scalable, persistent storage for analytics.
$0
per month
Pricing
Google Cloud AI
IBM Cloud Object Storage
Editions & Modules
No answers on this topic
One-Rate Plan
As low as USD $12/TB a month
per month
Standard Plan
Free up to 5GB—no minimum fee, pay only for what you use
per month
Offerings
Pricing Offerings
Google Cloud AI
IBM Cloud Object Storage
Free Trial
No
No
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
Optional
Additional Details
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The One-Rate and Standard service plans for Cloud Object Storage include resiliency options, flexible data classes and built-in security. Pricing is based on the choice of location, storage class and resiliency choice.
More Pricing Information
Community Pulse
Google Cloud AI
IBM Cloud Object Storage
Features
Google Cloud AI
IBM Cloud Object Storage
Infrastructure-as-a-Service (IaaS)
Comparison of Infrastructure-as-a-Service (IaaS) features of Product A and Product B
Google Cloud AI is a wonderful product for companies that are looking to offset AI and ML processing power to cloud APIs, and specific Machine Learning use cases to APIs as well. For companies that are looking for very specific, customized ML capabilities that require lots of fine-tuning, it may be better to do this sort of processing through open-source libraries locally, to offset the costs that your company might incur through this API usage.
In my experience, IBM Cloud Object Storage is well suited for projects like the one I am working on. This includes the use of natural language classification and the uploading of data to train a machine learning model for tag suggestions based on a body of text. Using IBM Cloud Object Storage has helped with this greatly. IBM Cloud Object Storage has also been great for Big Data Analytics thanks to its scalablilty and ease of use for large datasets. Alongside IBM Watson and our team's internal big data tools we've managed to process and analyze data more efficiently, leading to key insights that have driven business value for our clients.
IBM Cloud Object Storage is an excellent choice for disaster recovery and backup solutions. Its high durability and geographic redundancy ensure that our backup data is safe and can be quickly restored in case of a disaster. This capability is crucial for maintaining our business continuity and minimizing downtime. We have deployed our loads in an IKS cluster distributed in 3 different AZs with stateful data allocated in COS.
We have a video streaming application and need to store and deliver a vast library of video content to millions of users worldwide, so we store our data in COS, which is cheap and reliable.
We have a bunch of data that must be analyzed and stored in datasets for fraud detection, risk management, and customer insights. In these cases, this data is moved from Onprem to IBM Cloud so we can use cheap storage like COS.
Some of the build in/supported AI modules that can be deployed, for example Tensorflow, do not have up-to-date documentation so what is actually implemented in the latest rev is not what is mentioned in the documentation, resulting in a lot of debugging time.
Customization of existing modules and libraries is harder and it does need time and experience to learn.
Google Cloud AI can do a better job in providing better support for Python and other coding languages.
Searching and retrieving—full-text search or metadata search—is one of the significant areas of improvement. It isn't easy to search for data with this.
Integration with other IBM cloud services is trickier. For example, integrating this with API Connect to access the data from API will be difficult for users.
Support - I think you should have more support community.
We are extremely satisfied with the impact that this tool has made on our organization since we have practically moved from crawling to walking in the process of generating information for our main task to investigate in the field through interviews. With the audio to text translation tool there is a difference from heaven to earth in the time of feeding our internal data.
I give 8 because although it´s a tool I really enjoy working with, I think Google Cloud AI's impact is just starting, therefore I can visualize a lot/space of improvements in this tool. As an example the application of AI in international environments with different languages is a good example of that space/room to improve.
For my use cases, it has been a very smooth experience. Even my new colleagues have been able to get on top of things very quickly. This shows how easy it is to work with
We rarely face downtime or access issues with IBM Cloud Object Storage. It’s mostly available when we need it, even during peak hours or heavy data loads.
I would give it a 9 because it works smooth with our AI and analytics tools, no major slowdown. Pages and dashboards load fine most of the time, and reports finish in decent time even when data is heavy.
Every rep has been nice and helpful whenever I call for help. One of the systems froze and wouldn't start back up and with the help of our assigned rep we got everything back up in a timely manner. This helped us not lose customers and money.
I have been working in IT sector for more than 15 years. I have worked with various vendors. IBM's sales team, support team have been really helpful. After we start to use their product, their UX design team also contacted us to get feedback from us. They are really interested about our experience.
I just researching and applying the tools on their platforms to ensure a good learning path, based on my needs. Reading the documentation related with resources, tools. Is too big, but I am trying to know more about it every day. It is a good way to know more about their resources. A new way to attract new customers. At the end of the day, we are all involved in improvement and automation of our tasks and resources for customers and end-users.
In fact, you only need the basic tech knowledge to do a Google search. You need to know if your organization requires it or not,. our organization required it. And that is why we acquired it and solved a need that we had been suffering from. This is part of the modernization of an organization and part of its growth as a company.
Yes Our organization used IBM professional services to implement IBM object storage because of its data consistency and multiple way to upload and download data and its encryption security features. Also that its brand matter for the any organization to secure the layer and storage. It sis also verify that application and system are compatibale for this product
These are basic tools although useful, you can't simply ignore them or say they are not good. These tools also have their own values. But, Yes, Google is an advanced one, A king in the field of offering a wide range of tools, quality, speed, easy to use, automation, prebuild, and cost-effective make them a leader and differentiate them from others.
Amazon S3 is a great service to safely back up your data where redundancy is guaranteed, and the cost is fair. In the past I have used Amazon S3 for data that we backup and hope we never need to access, but in the case of a catastrophic or even small slip of the finger with the delete command, we know our data and our client's data is safely backed up by Amazon S3. Amazon S3 service is a good option, but based on the features it provides compared with IBM Cloud Object Storage, it is less suitable. IBM Cloud Object Storage is also integrated with more services, like IBM Cloud SQL and IBM Aspera, which AWS does not provide to transfer files at maximum speed in the world.
Scaling up the number of users can lead to significant increases in licensing costs, which, while not a technical limitation, can be a practical constraint for some organizations
Artificial intelligence and automation seems 'free' and draws the organization in, without seeming to spend a lot of funds. A positive impact, but who is actually tracking the cost?
We want our employees to use it, but many resist technology or are scared of it, so we need a way to make them feel more comfortable with the AI.
The ROI seems positive since we are full in with Google, and the tools come along with the functionality.
This allows us to recommend a platform to our clients that will quickly help them create new, efficient business processes with very little development.
This saves clients hours and days of manual analysis of images, allowing the system to do the work when attaching Object Storage to models.
There is a learning curve in utilizing the storage and the modeling, but once up and running, it works well during deployment.
