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
Redis Software
Score 9.1 out of 10
N/A
Redis is an open source in-memory data structure server and NoSQL database.
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VoltDB
Score 9.0 out of 10
N/A
VoltDB is an in-memory, scale-out NewSQL relational database from the company of the same name headquartered in Bedford, Massachusetts.
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Pricing
IBM Cloud Object Storage
Redis Software
VoltDB
Editions & Modules
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
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No answers on this topic
Offerings
Pricing Offerings
IBM Cloud Object Storage
Redis Software
VoltDB
Free Trial
No
Yes
No
Free/Freemium Version
Yes
Yes
No
Premium Consulting/Integration Services
Yes
Yes
No
Entry-level Setup Fee
Optional
Optional
No setup fee
Additional Details
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.
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More Pricing Information
Community Pulse
IBM Cloud Object Storage
Redis Software
VoltDB
Features
IBM Cloud Object Storage
Redis Software
VoltDB
Infrastructure-as-a-Service (IaaS)
Comparison of Infrastructure-as-a-Service (IaaS) features of Product A and Product B
IBM Cloud Object Storage
8.7
155 Ratings
6% above category average
Redis Software
-
Ratings
VoltDB
-
Ratings
Service-level Agreement (SLA) uptime
6.1143 Ratings
00 Ratings
00 Ratings
Dynamic scaling
9.8143 Ratings
00 Ratings
00 Ratings
Elastic load balancing
8.9140 Ratings
00 Ratings
00 Ratings
Monitoring tools
8.8144 Ratings
00 Ratings
00 Ratings
Security controls
9.8149 Ratings
00 Ratings
00 Ratings
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
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.
Redis has been a great investment for our organization as we needed a solution for high speed data caching. The ramp up and integration was quite easy. Redis handles automatic failover internally, so no crashes provides high availability. On the fly scaling scale to more/less cores and memory as and when needed.
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.
Easy for developers to understand. Unlike Riak, which I've used in the past, it's fast without having to worry about eventual consistency.
Reliable. With a proper multi-node configuration, it can handle failover instantly.
Configurable. We primarily still use Memcache for caching but one of the teams uses Redis for both long-term storage and temporary expiry keys without taking on another external dependency.
Fast. We process tens of thousands of RPS and it doesn't skip a beat.
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 had some difficulty scaling Redis without it becoming prohibitively expensive.
Redis has very simple search capabilities, which means its not suitable for all use cases.
Redis doesn't have good native support for storing data in object form and many libraries built over it return data as a string, meaning you need build your own serialization layer over it.
We will definitely continue using Redis because: 1. It is free and open source. 2. We already use it in so many applications, it will be hard for us to let go. 3. There isn't another competitive product that we know of that gives a better performance. 4. We never had any major issues with Redis, so no point turning our backs.
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
It is quite simple to set up for the purpose of managing user sessions in the backend. It can be easily integrated with other products or technologies, such as Spring in Java. If you need to actually display the data stored in Redis in your application this is a bit difficult to understand initially but is possible.
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.
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.
The support team has always been excellent in handling our mostly questions, rarely problems. They are responsive, find the solution and get us moving forward again. I have never had to escalate a case with them. They have always solved our problems in a very timely manner. I highly commend the support team.
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.
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
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.
We are big users of MySQL and PostgreSQL. We were looking at replacing our aging web page caching technology and found that we could do it in SQL, but there was a NoSQL movement happening at the time. We dabbled a bit in the NoSQL scene just to get an idea of what it was about and whether it was for us. We tried a bunch, but I can only seem to remember Mongo and Couch. Mongo had big issues early on that drove us to Redis and we couldn't quite figure out how to deploy couch.
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
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.
Redis has helped us increase our throughput and server data to a growing amount of traffic while keeping our app fast. We couldn't have grown without the ability to easily cache data that Redis provides.
Redis has helped us decrease the load on our database. By being able to scale up and cache important data, we reduce the load on our database reducing costs and infra issues.
Running a Redis node on something like AWS can be costly, but it is often a requirement for scaling a company. If you need data quickly and your business is already a positive ROI, Redis is worth the investment.