MinIO Reviews

MinIO is a very good system, and it's very suitable for people seeking an object storage system that is very similar to Amazon S3 and hosted locally. It's not in production yet, even though we have been working on it for years.

I haven't tested the solution's performance. I haven't done any heavy tests on the platform. We do not use the tool for really big data, but we use it for mid-sized datasets. The solution's performance is good. I can't complain about it because we don't have the best design.

I use the solution's basic object storage functionalities, like AWS S3 compatible APIs and creating buckets.

MinIO should provide an easier subscription model for companies that don't have a huge amount of data. Our company has a maximum of 100 terabytes of data. The solution should provide more bugging tools in the open-source version to encourage people to buy the support services.

It's not an easy decision. If I go to the management and tell them that I need to buy a service, there should be an easier subscription model for companies that don't have huge amounts of data. For me, getting a subscription for 15,000 a year for a system already in production might be a bit hard.

I think MinIO supports a minimum of one petabyte or 100 terabytes of data. Since we don't have such huge amounts of data, buying a subscription for the solution is a bit difficult. Hence, we're only using the open-source version for now. If MinIO becomes really crucial for our business, we could ask the management to get a subscription.

I have been using MinIO for two years.

MinIO is a stable solution.

I rate the solution’s stability a nine out of ten.

There are some limitations on the number of hard disks and nodes you can add to the solution. The solution works for small, medium, and enterprise businesses, depending on their data model. In an organization with a huge data set and requirements for big data, MinIO can be managed by a team or one or two users.

I rate the solution’s scalability an eight out of ten.

The solution's initial setup is really easy and straightforward. I have done stand-alone setups in Linux, Docker, Docker Compose, and Docker Swarm.

We use the solution's open-source version.

MinIO's cloud version has a couple of competitors, like Google File System and Amazon S3, which are cheaper than MinIO. There are no alternatives to MinIO's on-premises version. There are some, but they have a different model. What makes MinIO unique is its compatibility with Amazon S3.

The solution's integration with AI tools is very easy, and I rate it ten out of ten. Because of Amazon S3 compatible APIs, what works with Amazon also works with MinIO. I have tried this often in many use cases, and it seems good. I would recommend the solution to other users.

Overall, I rate the solution a nine out of ten.

We use MinIO as a cloud storage solution specifically for our data science team. It helps us share data and organize segregation of duties and security rules based on the S3 API and credentials. We leverage it to manage access and role-based models, among other tasks.

We use MinIO as a cloud storage solution, which is easy to integrate with our data science tools. This means our data scientists can handle extensive data processing and analysis more seamlessly.

MinIO is easy to install and use, especially for standalone installations. It supports S3 API integration, which makes it compatible with various data science tools and simplifies the organization of storage classes in Kubernetes.

The main issue we face with MinIO is performance. We need higher I/O capabilities for extensive data read-write operations, especially when dealing with big data and Parquet formats. The issue might be related to our simple deployment setup, but it still affects usability.

We have been using MinIO for about six months.

MinIO is generally stable, but we have noticed occasional performance downgrades when our data scientists perform extensive data read-write operations. We need more observability and monitoring to understand these occurrences better.

We are not happy with MinIO's performance scalability, as we need more I/O capabilities to handle big data.

I personally have not contacted MinIO's technical support, but I know some colleagues who have, and they were generally happy with the service.

Neutral

The initial setup of MinIO is straightforward. It took us about a week, which included discussions, reconfiguration, and running tests.

Our IT team, comprising a few members, handled the installation and initial setup.

It's hard to compare pricing as we are looking for a solution that includes vendor support, which would ensure reliability and ease of operations. Comparing MinIO to other vendor-backed solutions is challenging in this context.

We evaluated other vendors like Dell for their monitoring and support capabilities.

I'd rate the solution seven out of ten.

My company uses MinIO for storage purposes and as a replacement for Amazon S3.

MinIO has helped speed up the processes carried out by my company's developers.

The most valuable feature of the solution is that it offers features similar to the ones offered by Amazon S3. In my company, we needed a tool that we could deploy on a hybrid environment consisting of a private cloud. The solution's use in a hybrid environment is great.

MinIO can make it easier to install the product in an OpenShift kind of environment. I think it's a little bit tricky to install MinIO in an OpenShift type of environment.

I have been using MinIO for three years. I use the solution's latest version.

Scalability-wise, it is a good solution. I rate the solution's scalability a seven or eight out of ten.

I have experience with Apache Hadoop, Amazon S3, and Microsoft Azure. My company uses MinIO due to the cloud-related capabilities that it offers us.

The product's initial setup phase is complex.

The solution is deployed on a hybrid cloud.

One or two people can deploy the solution over a period of two months.

I cannot say if I have seen a return on investment from the use of the solution since it is not a paid product. My company uses the open-source version of the product. The product does save time for our company.

My company hasn't tried the version of the solution where we need to pay to use it.

MinIO requires maintenance. One person is required to take care of the tool's maintenance part.

I recommend the solution to those who plan to use it.

I rate the overall product a seven or eight out of ten.

We host a document store with approximately seven million documents that need to be retained in perpetuity. The documents are used for discovery in legal cases. The document store grows continuously and periodically they have been rehoused due to scalability issues. We selected MinIO because it promises to be a more highly scalable and performant solution than past choices.  We are users of MinIO and I'm the VP of Information Services as well as the company CTO. 

We're currently running MinIO in parallel to an existing object store as we migrate to it. Object retrieval with MinIO is much improved over the prior solution, updates are simple to apply, and we anticipate that future capacity requirements will be easier to meet.  Our customers are using this solution to retrieve tens of thousands of objects (documents and files) per hour, and MinIO seems to be able to keep up with it.  While we migrated all 7 million objects we are performing a byte-by-byte validation before removing them from the old system - a process that is not expected to be completed before the end of the year. From a management perspective, once we get the object store validated, we're going to be able to set up a seamless synchronization with our offsite data store in Amazon S3 with the built-in functionality for mirroring buckets, which will provide a huge improvement over the existing application.

The retrieval performance of objects with MinIO is significantly higher than a lot of the alternatives we investigated. We're able to use  Amazon's SDK to interact with it, and the SDK support is excellent. The included MC tool is not only good at administering MinIO, it is also good for administering our S3 buckets, as it's actually more capable than Amazon's own tool. Updates are also very simple and easy. We've done numerous updates since the deployment and the platform stays online throughout, which is an unexpected bonus. I think in terms of other useful functionality, there are some very good things about it.

Improvement could be made in several areas. When implementing a distributed solution, there were no good white papers or tutorials on implementing clusters, so we had to kind a of wing it, and it took us a while to get the clustered implementation working. The clustering documentation is oriented towards containers and Kubernetes, and we're running Linux VMs instead of containers, partly because we run on top of VMware and it's a little easier to manage a VM than it is a container in VMware's platform. We're also using vMotion and we have a cluster of VMware hosts which approximates the functionality of containers without the complexity, plus we have SAN on the backend. Containers actually create a degree of complexity that's unnecessary for our application because we already have a great deal of hardware redundancy in our system. 

There's very little documentation on performance tuning for MinIO and for running it on Linux, which has been problematic because as the object store has grown, we've run into various performance issues. We've done a lot of our own research and some of our own performance tuning on a trial and error basis.  We've had intermittent latency on object retrieval on a sporadic basis, and no way to determine the underlying cause.  There have also been some technical issues. When we added more than 100,000 objects into a single bucket, the web browser interface for viewing buckets became unusable, which means we have no graphical way to search or browse our buckets, and have to rely on programmatic means.

We were initially using Prometheus, which extracts performance and usage data into Grafana for monitoring. That was useful until we exceeded a million objects and then it stopped working correctly. We were unable to get accurate statistics out of the system, and had to come up with a workaround by creating bucket notifications, that can be forwarded to a database. We're using a MySQL cluster for that, aggregating bucket notifications into MySQL and then parsing the JSON data out of MySQL to do our own dashboarding to keep track of performance and utilization issues. It seems to be working, but none of the native interfaces for MinIO work when you exceed a certain bucket size. 

We then had two other issues we ran into: There's a supposedly optional heal function, but in practice that's not exactly the case. It's extraordinarily slow. We started a heal run about two weeks ago, and it's only done about 7% of the documents in the last two weeks and it's still running. Secondly, the SSL implementation was a more complicated than it should be. We had wanted to secure the documents for access, because we use a suite of web services we developed ourselves with the Amazon SDK for providing CRUD operations on objects. We needed to secure it with SSL, but we ultimately found it was a lot simpler to front MinIO with NGINX as a proxy, and keepalived to provide automatic failover, than the solution they had suggested. We came up with our own SSL solution, but it was not easy. 

It would be nice if there was a graphical tool for searching buckets that didn't attempt to display the bucket. We use a product called Couchbase, which is based on CouchDB as a key value pair database for one of our web applications. It has a very nice function for searching buckets by key - something comparable in MinIO would be great. I think also that improving the logging functionality to enable more selective statistics logging the way that bucket notifications work would be very valuable. One step further - outputting statistics data in other formats would also enable better monitoring. Fixing the heal function - or perhaps allowing it to run across the cluster in parallel instead of only on a single node - would be valuable.  

1 Year

The solution seems to perform fairly well under load. There have been occasional issues with unexpected latency developing and we've been trying to pin that down, but we don't have any tuning documentation to allow us to do that. It's basically been a hit or miss proposition to figure out what's causing the intermittent performance issues. MinIO doesn't seem to require a lot of maintenance. We have a network operation center and they've been able to keep a pretty good eye on it using a workaround we devised. We haven't had any outages so I'd classify it as stable. 

The biggest bugs are in the web browser interface, and the failure of Prometheus when it didn't scale. The web browser interface won't let Prometheus scale correctly in large buckets. But I don't imagine people are typically putting seven million objects in a bucket like we are. That's a lot of objects and the average size of the binary is at least a megabyte. In some cases it's 10 megabytes and they are fairly large binaries to be shuffling around. Those are the major problems, but also the heal function is inordinately slow. Other than that, the application performs fairly well.

Internally, it's the backend for our document system and the content management system.  The document management system is used by our entire staff of approximately 40 people. It's role as a content management system is used externally by our customer base, which is  approximately 10,000 people a day. We have a number of other potential use cases and once we've completed migration from our old object store, we're going to explore those. Presuming they can resolve some of the issues in upcoming releases, it'll have a lot more utility in the organization. Unstructured data has always been a challenge to deal with in content management systems and we have a lot of unstructured data in our business. There's a range of different applications where that's valuable.

We haven't taken advantage of the technical support but we have used their support forums and had some responses, but I believe it's a fairly small team at MinIO and I don't think they have a lot of people involved in support yet.

Our data was all previously stored in a SQL Server AG cluster, but the performance in moving binary objects in and out of SQL Server is fairly poor, and database backups for multi-terabyte databases within maintenance windows very challenging.  MinIO is an S3 compatible object store that mirrors seamlessly with Amazon and other S3 object stores, and doesn't have the management problems that go with a large SQL Server installation. There are a lot of complexities in managing a large document store in SQL Server because it's not a great solution for storing binary large objects - blobs, as they're known. Programmatically, the .NET support for putting data in and out of SQL Server is quite good, but not the performance. It's slow and backing up such a large database exceeds our backup window. Effectively, we were never able to back up that database. We had to create a process to continuously extract new data out of it and to place it offsite in Amazon, but the backup and restore processes were slow as a result. It created a lot of headaches for our DBA. It was a 10 terabyte database and SQL doesn't deal well with such large databases.

The initial setup involved two people - a network engineer to setup the backend VMware infrastructure, and then the Linux VM deployment which I performed myself. Although I'm the CTO, I'm fairly hands-on because we're a smaller company and I have deep Linux expertise that goes back to the 90s, so I implemented the various nodes and set up all of the information around replication and configuration. My network engineer set up the VMware hosts and tuned the storage backend and a number of other things. It was a collaborative effort.

If we'd had better resources, we probably could have done it in about two weeks. But we had a few false starts and had to basically make it up as we went, so it took about six weeks to get the initial deployment working.

We did not utilize outside vendors.  For mission critical applications we always develop inhouse expertise.

Since the product is not technically in production, a ROI can't be computed

We are using the open source version, so we didn't pay anything for it. We are planning to obtain a support contract when it's fully in production - which is to say once all of our documents have been validated, and it's stable in our environment. Looking at the prices, they seem to be fairly comparable to what we've paid for similar products in the past so there's no issue paying for support and product, but we're still at a step beyond the proof of concept stage. That won't be complete until we validate that all the binaries are correct.

In terms of additional costs, a lot of hardware went into this. We're running it on a cluster of VMware servers. There were licensing costs for the VMware host and in addition to that, we're running it on a storage area network on the backend and the storage area networks alone are very expensive. It's a fairly large storage area network too, so we're essentially running it on dedicated hardware. Our investment to date exceeds $200,000.

We compared MinIO with a number of other object stores and it offered some performance advantages and a degree of simplicity which was very appealing. We implemented a four server failover cluster and we migrated all of the documents into MinIO which took us about three months. We're currently running a validation process before we remove the old object store by doing a byte by byte comparison of the objects from the old store and the new store. Because it's such a time-consuming process, it's only about 25% done and we anticipate it'll take another three or four months before it's complete.

As the solution evolves, it will become a better product, but right now it has a lot of rough edges. I would not recommend implementing MinIO unless you have sufficient technical expertise. I'm very familiar with non-relational as well as relational databases, and with Linux, which helped during implementation, but not every shop has that skill set available. I was able to extrapolate what it should be doing based on the type of product it is and comparisons with similar technologies that I've dealt with in the past. Without that experience I think it would be difficult. If you're doing a single server implementation, it's very simple but it gets complex very quickly if you're building a clustered server, which is what we were doing.

I rate the solution 7 out of 10. I would rate it higher if the management tools were usable on large buckets, and the quality of the documentation was higher.

I like that if you have a problem, you can buy the home server. It is stable and robust.

The solution should have high availability. Also, support should be quick.

I have been using MinIO for two years.

The product is stable. If you buy the SSD, then it's good.

I rate the solution's stability a nine out of ten.

The solution’s scalability is good.

100+ users are using this solution.

I rate the solution’s scalability a seven out of ten.

MinIO provides community support. We can find the solution from the community, but it takes a few weeks to get the answer.

MinIO is easy to use and works with another connector.

The initial setup is easy and takes one to three hours, depending on the infrastructure. To deploy, download the container and then deploy it on our infrastructure.

I rate the initial setup an eight out of ten, where one is difficult, and ten is easy.

The product is free of cost.

I rate the solution’s performance as seven to eight out of ten.

Overall, I rate the solution an eight out of ten.

The tool helps our customers store documents with their respective versions. Our solutions work around loan processing, loan origination, loan management, and collections. During the loan application process, there is a lot of documentation involved which needs to be stored. The product handles the document’s versioning and storing.

Our solutions also have a module that does the video KYC of our customers. MinIO saves the actual recording of the video KYC process. We use the tool to store and retrieve documents and videos with proper versioning.

The tool’s integration is very easy. This feature has helped us reduce development time. The solution also has many out-of-the-box features like versioning support and management of roles and permissions. The product also supports clustered deployment.

The tool’s pricing needs to improve. We also encountered challenges while deploying the tool in Kubernetes. The documentation also was not too great. We have currently deployed the solution in a stand-alone fashion.

We have been using the solution for two and a half years.

The product’s stability is pretty straightforward.

The tool is scalable. It supports clustered deployment which we haven’t used. However, we wrote the documentation and did an internal POC where we deployed it in the test clustered fashion.

We are using the tool’s free version. The free version does not come with any support. However, you can get support from the tool’s strong community. We haven’t run into any issues that require extensive support.

It is difficult to deploy the solution if you involve Kubernetes. The setup is easy otherwise. I believe that it shouldn’t be an issue with the tool’s latest version. The good part is that the tool supports multiple storage technologies

The product has pretty good documentation available on their website which our DevOps team followed and successfully deployed the solution. My team downloaded the binaries from the library, executed them, and made some initial configurations.

The deployment was pretty quick and we were able to complete the process within a couple of days. The Kubernetes part took weeks to complete. You just need a resource with a good understanding of the documentation and experience in Linux technologies to do the deployment. A team of two to three members can complete the deployment in a week’s time.

I would rate the tool an eight out of ten. We use the solution’s community version. My company is the implementer of MinIO and not the end user. We are a fintech company that provides digital lending solutions and digital onboarding solutions to banks and financial initiatives. When we deploy our solutions, we also implement Document Management Systems as part of our solutions. These Document Management Systems use MinIO as the core object storage.

We have not found any issues in the tool’s maintenance. You can get pretty good object storage with the community version. The tool has good capabilities in the enterprise version as well. I would definitely go for MinIO over other technologies.

I am a solutions architect. MinIO is a public cloud type of storage that can attach external storage volume. I run it proprietary, or open-source. I use it to run a lot of test instances and production, spinning a new product out of it. In general, I use it for the S3 cloud storage capabilities.

Internally in our company, we have five people that use MinIO by putting their data in and heavily pound it for testing efforts.

With different types of storage, MinIO enables me to create these storage volumes called buckets, this is an S3 type cloud storage, I can attach these cloud buckets to different types of storage and actually create levels, or tiering of options of storage levels. If you were using Dropbox, I can attach a cloud storage volume to that Dropbox and it can be publicly shared as opposed to you having to do a file sync and share with basic storage.

The container installation features are good. The S3 feature provisions the storage buckets making it easy. It allows me to spin up the public buckets with open-source technology.

Another valuable feature of MinIO is Erasure Coding which is comparable to enterprise-based systems.

The MinIO dashboard is minimal as there are only a couple of features inside the dashboard for a basic user. I would like this to be more robust with more click-around features.

It is important that MinIO continues to increase its performance. With the increased scaling of specific research coding and the specific throughput the features currently work well, however they need to continue to maintain that community.

The stability of MinIO is great. It is a software defined storage that will manage everything well if everything is configured and setup correctly.

MinIO is very easy to scale as it is scale-out architecture. If I need more performance, more memory, or more discs I can add another virtual machine and it attaches to it nicely. 

MinIO is open source software. It is community based so its developed by the community.

I was using Amazon's S3 and nothing really seemed to work as well as this, until MinIO, the product is comparable. The main reason I switched to MinIO was that it is open source.

Deployment of MinIO depends on what you are trying to accomplish. In my case, it is a four-node cluster with a minimum of four servers, and took myself, a senior cluster role, a full day. The biggest complexity is how you configure the storage around this. You can storage attach, which can get complicated making it an intermediate level of deployment.

This solution is maintained in-house however, there are a lot of factors around that. MinIO manages disc failure, so you need to have hot spares of failing hard drives. You also need to maintain your operating system to make sure that the caching is running optimally and that you get your updates and patches on. Within MiniIO, I look at the caching between the discs. Sometimes you can have files that lock and are holding something up on a certain file.

MinIO is open source so it is free.

Hitachi HCP is an option that I compared MinIO against.

Our intention is to rollout MinIO as an enterprise, product offering, to customers. It will be part of a big ecosystem of cloud-based storage. If a company is coming off object storage, or if they were looking at Hitachi HCP be sure that you deploy with your Erasure coding and look into the caching configuration.

As far as functionality and stability on the backend of MinIO I would rate it an 8 out of 10. 

We use the solution for object storage in our core platform. It works best as a data lake solution for us.

The solution is simple to use and maintain for DevOps executives. Also, it has the best performance compared to other solutions.

The solution's features for distributed non-container applications and reverse proxy could be better.

I have been using the solution for three months.

It is a stable solution. I rate its stability ten out of ten.

It is a scalable solution. It uses consistent patching; thus, it is more scalable than other solutions. Although, we encountered a few scalability-related issues while introducing a new node.

We used Azure solution before. It was challenging to maintain the Kubernetes cluster.

The solution's initial setup was straightforward. We deployed it through Ansible playboards. It took about three days to complete.

We use the solution's open-source version.

I recommend the solution to start-up businesses. It is the best tool in the market if they want a simple and low-maintenance product. Also, it requires DevOps expertise for the smooth functioning of scalability and reverse proxy features.

I rate it eight out of ten.

I mainly use MinIO to store and process unstructured data like customer receipts.

The developer support could be better.

I've been using MinIO for two years.

MinIO's stability is pretty much okay.

MinIO is scalable.

We've used the UI interface and community practice and tended to get a response back within a couple of days.

Previously, we had a Hadoop-based database, but the tools and the community service to manage the Hadoop clusters were too expensive.

The initial setup was straightforward as MinIO provided good support documentation and took a couple of days to complete. I would give MinIO a rating of eight out of ten.

We evaluated Cloudian and RedHat.

MinIO's architecture is very simple, but since it doesn't go with any particular hardware, sometimes they rely on outside software. 

We are using this solution as a data link, to store data in a structured dataset. We've been testing the functionalities and how we can integrate our system into it. We are customers of MinIO and I'm a data scientist. 

This is an all-in-one, user-friendly data storage solution. It provides high throughput to access data. We tend to use AI and some of the resource-intensive applications related to data, like analysis and visualization. I like the S3 API.

I feel there is a lack of good addons to integrate without having to use third-party applications. It makes the process time-consuming. It would be helpful if MinIO built artifacts or anything that could be used to stream data into it. That said, I'm not sure MinIO is different from other solutions. Hopefully, data governance will improve in the future. I'd also like to see more support for AI. 

I've been using this solution for four months. 

I can't judge stability yet because we're only using a couple of megabytes or gigabytes, it's very small. We probably have three or four potential users in the company. 

I previously worked with Hadoop which I found to be a little bit more complex than MinIO which is easier to use. I chose MinIO because I like the S3 API. We were looking for an all-in-one solution to backup or to carry out disaster recovery, and to have a place where we can store a new dataset for analysis and something for big data and AI.

I generally recommend it in favor of Hadoop Distributed File System because I can see more benefits and it's a little bit cheaper if you download it on-premises compared to Amazon S3.

The standalone is really easy to deploy. I think we'll deploy four nodes and I'll use Docker Swarm for that.

We are using the free version. This is still a new system and I think it's a good idea to have a free version to test before purchasing a license.

It's difficult to comment on the product because we haven't completed testing or deployed it in the production environment.  Moving to MinIO involves a learning curve. It's a question of whether someone is prepared to put in the effort to learn the solution and whether they have sufficient experience. The decision to use it needs to be based on whether it's for backup only or for backup and disaster recovery. Then there's the option to use it for analytics and AI, which is more complex and requires integration with other tools.

Once the solution has more maturity, I think it will become a dominant product. For now, I rate it eight out of 10.