Amazon AWS CloudSearch Reviews

The main use case for us was to search the operational records from our company databases and perform full-text search across operational records and uploaded documents. We needed something where users could search by keywords, IDs, partial names, and filters without building a custom search engine from scratch. Most of our traffic is moderate, not huge-scale, probably a few hundred thousand searchable records with steady daily queries. It fit well for that middle-ground use case.

Integrating Amazon AWS CloudSearch into our application for those operational records was mostly straightforward.

The features of Amazon AWS CloudSearch helped our team significantly by saving us from managing Elasticsearch or OpenSearch infrastructure ourselves. We did not have dedicated DevOps resources for search, so having patching and availability handled helps reduce operational overhead and our time.

For example, it took much more time before using this feature, but after using this feature, we are managing it better. It mainly saved our team from managing Elasticsearch or OpenSearch infrastructure ourselves. We probably avoided a decent amount of engineering time that would have gone into maintaining a self-hosted setup. The faster search experience also improved usability for support teams internally.

Support teams spent less time manually filtering records or retrying searches. It simplified maintenance because nobody had to babysit the search layer daily.

Improvements for Amazon AWS CloudSearch can be made, but I will first start with the biggest improvement. The biggest improvement area is that Amazon AWS CloudSearch feels a little older compared to newer AWS services. The second thing about improvement is the documentation. The documentation could definitely be refreshed with more practical examples and troubleshooting scenarios. During setup, a few indexing issues took longer to diagnose because error messages were pretty generic. Better debugging visibility would reduce trial-and-error work.

Monitoring is decent through Amazon CloudWatch, but I would like more detailed search-level diagnostics out of the box. Sometimes it is not obvious why certain queries rank results differently unless you manually test a lot. More transparent query analysis, indexing, and insights would be useful. Logging exists, but deeper visibility would help during optimization.

I have been using Amazon AWS CloudSearch for around the last year, mainly for the search functionality inside an internal web application.

Amazon AWS CloudSearch's stability has been pretty solid. We have not had major outages related directly to Amazon AWS CloudSearch during the time we have used it. Once indexing pipelines were stable, it mostly ran quietly in the background. That reliability was one of the most outstanding experiences we have ever had.

Amazon AWS CloudSearch's scalability for our medium-sized enterprise handled growth reasonably well. Performance stayed consistent for our workload. For our organization, it was pretty good.

The customer support for Amazon AWS CloudSearch is something we only contacted AWS support a couple of times, mostly around indexing behavior and configuration questions. Response quality was pretty superb, though sometimes it took a bit to get very specific technical clarification. Nothing negative overall, but not exceptionally hands-on either. Most issues were resolved eventually.

Before Amazon AWS CloudSearch, we were mainly using our custom search logic from our database. This custom search logic was really slow and took much more time compared to Amazon AWS CloudSearch. That approach became slower and harder to maintain as the dataset grew.

Before choosing Amazon AWS CloudSearch, we evaluated other options. We looked at Amazon OpenSearch Service and self-managed Elasticsearch. OpenSearch definitely had more advanced capabilities, but it also required more operational attention and configuration knowledge.

Setup was fairly smooth overall. Pricing was understandable once we estimated indexing volume and query traffic. Initial schema setup required a bit of experimentation, but after that, it was manageable. Overall, the experience was good.

The ROI mainly came from reduced operational effort and faster implementation. We were spending weeks before; the engineering team was spending weeks building and maintaining a custom search stack from our database. But after purchasing this, we have seen our time has been reduced and our operational cost has also been reduced. It also reduced support friction internally because users could find information faster.

We purchased Amazon AWS CloudSearch through the AWS Marketplace. Pricing was understandable once we estimated indexing volume and query traffic. Though it can grow if you scale instances aggressively, for smaller to medium workloads, the cost felt reasonable compared to managing infrastructure ourselves.

We looked at Amazon OpenSearch Service and self-managed Elasticsearch. OpenSearch definitely had more advanced capabilities, but it also required more operational attention and configuration knowledge. We also briefly considered Algolia, but pricing and integration preferences pushed us toward AWS.

Amazon AWS CloudSearch is practical and dependable for teams that want managed search without a lot of infrastructure management. It may not have the newest features compared to other search platforms, but its stability and simplicity make it easy to adopt. For small- to medium-sized applications, it handles search very well compared to our old custom logic that searched data from our databases. I would probably not use it for heavy or complex search analytics workloads, though.

My advice to others looking into using Amazon AWS CloudSearch would be to consider it if your requirements are relatively straightforward and your team wants low operational overhead. Spend some time planning your schema and searchable fields early because changing the structure later can be annoying. It works best when you keep the implementation simple. Also, test relevance tuning with real user queries instead of relying only on defaults.

One thing I appreciated about Amazon AWS CloudSearch was the schema flexibility once you understand how fields are structured. The API side is also pretty simple compared to some heavier search platforms. It is not the most feature-rich search product out there, but for straightforward search requirements, it stays manageable. I would rate this product eight out of ten overall.

The biggest improvement area is that Amazon AWS CloudSearch feels a little older compared to newer AWS services. Some advanced search capabilities and analytics are more limited compared to modern OpenSearch setups. It still works reliably, but it does not feel like a product AWS is heavily evolving anymore.

I am just working for my organization, and my organization has around 118 clients. All of our clients are into AWS Cloud. So we are accessing them and providing the solution to them with regards to issues, especially with any regular issues related to the technical side.

We have PeopleSoft Integration Broker, which is the middle layer technology we are using, and we use AWS because all our clients are in the cloud. While accessing their system, we depend on AWS using our code. It means we have some predefined codes in PeopleSoft. Using PeopleSoft Integration Broker, we are accessing them for data exchange. Basically, we are accessing the business logic. We are providing solutions to our client's regular issues.

In terms of what needs improvement, I would say that it needs to keep its cost competitive in the market, especially in comparison to other clouds. Let's say we have various clouds in the market, like Google Cloud, Oracle Cloud, and AWS Cloud. However, security-wise, I don't think AWS is bad. It's good only, especially in comparison to Oracle Cloud, if you really use Oracle, while also considering the fact that PeopleSoft is an Oracle product.

AWS is a separate cloud, and Oracle has its own cloud. If you are in a new PeopleSoft and Oracle and you are using a third-party cloud, it means it is not easy since we can't think it is easy. I mean, if you are using Oracle products and you are using Oracle Cloud, it will be easier for you. However, it has a cost in comparison to AWS. Oracle Cloud is too costly. According to region, we segregate because it depends on the organization's strength. Let's say your organization has 1,000 customers. In that case, on a daily basis, let's say one customer was released or discontinued using the product. Then, you have to remove the solution. However, if you use Oracle Cloud, that space will remain there. In the case of AWS, they will immediately cut down their space, meaning in terms of reuse ability, it will reduce the cost. In our case, AWS is the best in the market, actually. We have various clouds like Google Cloud and Microsoft Azure Cloud, the features of which are very different.

There are a lot of features in AWS Cloud since I am not in the market providing service on the products. I am just using that tool to access our clients' database and deliver our day-to-day service. I interact with the clients regarding their issues, whatever they are facing. There is this one kind of interface we use to access things because they are in AWS Cloud. If your customer is in Oracle Cloud, then there will be a different approach to accessing it. In our case, we can use AWS or Oracle, so it doesn't matter to us.

I have been using Amazon AWS Cloud Search for two and a half years. I work with PeopleSoft, but I use AWS to interact with the client database. I am a PeopleSoft techno-functional consultant. I am a solution provider.

Considering stability, it will be in the market for a long time because Amazon is going to upgrade again and again. They are upgrading their systems and products. Even Amazon, in the market, is introducing its own ERP. AWS will not die. It will remain alive in the market. The solution will be stable in the market.

Scalability-wise, I rate the solution between eight to nine out of ten. It is a scalable solution. Also, it is a very good tool. It is better in comparison to other clouds. Nowadays, all the clouds are in the upgrade mode. They are giving a few things depending on the customer feedback. According to that, they are upgrading the solution. Hence, they are providing value-added solutions.

Speaking about technical support, once you have provided the interface to AWS, then that's it. It provides us with the ability to reuse it. We can use the same tool. There is no need to change the code, especially when speaking from a technical point of view. It is reusable.

I use Oracle Cloud and AWS, but I am more into AWS. At my current organization and in my previous organization, I have worked on AWS. Only in one organization, Credit Suisse, I worked on Oracle Cloud.

On a scale from one to ten, where one point is a difficult setup and ten points is an easy setup, I rate the setup as an easy one. The workstation is easy to set up.

The solution can be on different clouds, public and private. It can be used in your work according to your goals. Facebook is on an open cloud, and similarly, you are going to provide access to the user, whether in a public gateway or in a private gateway. If you are accessing secure data, then obviously, you have to keep this on the private cloud. Hence, it all depends on the security.

Regarding the deployment process, we have videos in the market. With AWS Talend, only one or a few resources are required to deploy the solution. But in other clouds, if you think about other clouds like Oracle or any other cloud, I am not sure about the deployment process. If you are using Oracle Cloud, it requires multiple resources, so we need more resources for deployment. In the case of AWS, one resource can do all the deployment activities in multiple regions. One can use one resource during the day shift and another resource during the night shift. Two resources can work all over the world, wherever you have your customers.

On a scale of one to ten, where one point is cheap, and ten points are expensive, I rate the pricing as medium or reasonable. In comparison to other clouds, you can find a free cloud too. However, according to the scalability, stability, reliability, security, and features, you can consider that cost-wise, it is medium or reasonably priced.

One is supposed to go for Amazon AWS CloudSearch since, with other clouds, it will take time. For example, if you have 1,000 employees in your company. On a daily basis, a few employees are joining, and a few others are being released or resigning. The resource they are using in the cloud with Amazon is immediate and easy to release the resources with immediate effect, but in other clouds, it won't be possible. If you are releasing the resource, it means you are paying to the cloud for the web space. If you are expecting that, you need 10 GB of space, and you are utilizing 10 GB space with some strategic resource to the employee with whatever you have. Each time you are utilizing, let's say, ten employees are released from the company, and five to ten people are joining the company, while you have 10 GB, and you may require 10 GB more. In that case, you can utilize the balance or make it balanced. In such a case, the cost will be reduced.

Considering that the solution's use cases may depend on and vary from organization to organization, I rate the overall solution a nine out of ten.

We use it as our hosting solution, serving as the backbone for our systems, which include Rubrik and SAP.

It is remarkably efficient and beneficial.

A reboot should be enhanced. There are issues with the VBC collection.

I have been working with it for four years.

I would rate the stability ten out of ten.

It is highly scalable. I would rate it ten out of ten.

The technical support is highly beneficial.

We had previously employed IBM. IBM's support proved to be excessively costly, leading us to opt for Amazon.

We have migrated from on-premises to the cloud.

We used a third-party service, an Amazon partner, to assist with product support, installation, and configuration. Based on the size and internet speed, we've established a network of around two hundred gigabytes in eight hours. It took us approximately twenty days to complete the migration.

In comparison to IBM and Microsoft, the pricing is more favorable. I would rate it eight out of ten.

I would recommend it. Overall, I would rate it nine out of ten.

I've only used the solution on a personal basis.

The cloud storage and cloud applications are the most valuable aspects. We have several applications we are testing to see if we have them on the cloud, including SQL servers and SAP HANA. We want to take advantage of cloud backups and migration. We're gathering information on databases and analytics. 

The stability is great.

I've found the solution to be very scalable. 

The initial setup is straightforward. 

We'd like to see more database features. 

We'd like them to lower the licensing costs.

It's hard, sometimes, to get the right person to help you when you get support.

I've been using the solution for approximately one year. 

It is stable and reliable. There are no bugs or glitches. It doesn't crash or freeze. I'd rate the stability nine or ten out of ten. 

The solution is very scalable. I'd rate it ten out of ten. 

We have about 50 people using the solution. 

We plan to increase usage. 

Technical support is okay. The issue is getting the exact person to actually handle the problem effectively. 

Neutral

We did also work with VMware and Microsoft. We wanted something with better ease of use. 

The initial setup is very easy AWS, in general, is very easy to set up, manage, and migrate. It's all very straightforward. I'd rate the ease of implementation ten out of ten. 

The deployment takes about one year. We went through a few stages over the course of the deployment. We started with procurement. We're a government institution, and it takes about six months to get everything aligned before deploying. 

We had four people handling the deployment: two from our end and two from the vendor partner. 

The maintenance requires about four people as well. We maintain the same team for deployment and maintenance. 

We used a third-party vendor to assist with deployment. 

We have witnessed an ROI. It is worth the month. 

The pricing is okay. It's moderate. I'd rate the solution five out of ten in terms of affordability.

We do annual licensing. I'm not sure how much we pay a year. It might be around $30,000 a year. 

We're currently also looking into Azure options. 

I'm a customer and end-user. 

I've been using the latest version of the solution. 

We are using a cloud VM solution at the moment, and we want to migrate our infrastructure to the cloud. 

It's easy to license and deploy. I'd rate the solution ten out of ten. 

We have deployed it for one of our clients. It is for custom-managed services.

They are using it for Autocomplete Suggestions and Fail Waiting Geostatical Search.

Everything with the solution is fine. I'd give it five stars.

The solution supports 34 languages. 

The initial setup is straightforward. 

It offers good stability.

We can scale the product.

Technical support is great.

Pricing is fair and reasonable. 

I do not have any suggestions for improvements at this time. 

I've been using the solution for five years. 

The stability is excellent. I'd rate it ten out of ten in terms of reliability. The performance is good. There are no bugs or glitches. It doesn't crash or freeze. 

The scalability is good. I would rate it nine out of ten in terms of the ease of scaling.

Technical support is fine. There is no issue in terms of getting help if we need it. 

Positive

The solution is very straightforward and simple. I'd rate the ease of setup ten out of ten. We have one or two staff members that can handle the initial setup process. 

Once it is set up, it does not require any maintenance. It's cloud-based, so maintenance happens automatically. 

So far, we have witnessed 100% ROI while using this product. 

We have found the product to be affordable. It is not overly expensive. I'd rate the affordability ten out of ten. 

We're an Amazon partner. 

I'd rate the product ten out of ten. We are happy with the service. 

I'd advise others to talk to an AWS Amazon solutions architect before implementation. A company needs to understand the solution and what it can do before jumping in. Once they understand the benefits and the process of deployment, then they can begin. 

There is a lot of training available online, specifically on Youtube and also on the Amazon portal for CloudSearch. Users can easily begin to educate themselves on aspects of the product. 

Amazon AWS CloudSearch can be used for storing a large amount of unstructured data, such as images, videos, or complex data.

The most valuable feature of Amazon AWS CloudSearch is its ability to receive data quickly. You can access your data easily in a short time.

The price of the solution can be expensive.

I have been using Amazon AWS CloudSearch for approximately six months.

The stability of Amazon AWS CloudSearch is good.

Amazon AWS CloudSearch is scalable.

We are using Amazon AWS CloudSearch for only development purposes, and there are a few particular system engineers impacting their development. We are not using it in production. When we are finished we hope to have approximately 100 users using it.

I have not used the support from Amazon AWS CloudSearch.

We previously used Microsoft Azure.

The initial installation for Amazon AWS CloudSearch is simple, you only need to configure it since it is in the cloud. 

It took me approximately 30 minutes to do the configuration at the beginning. After some experience, I can now do it in five minutes.

I can do the implementation myself. We have one engineer for the maintenance and support.

Amazon AWS CloudSearch charging is based on how many resources you consume or and the solution is known to be a bit expensive.

I would recommend this solution, but it depends on what service you are going to provide.

I rate Amazon AWS CloudSearch a nine out of ten.

I mainly use AWS CloudSearch for cluster-based AWS, EC2 services, cloud-front services, and Amazon Kubernetes services.

AWS CloudSearch's best features are good performance under high CPU and memory use, and ease of deployment and scaling.

AWS CloudSearch's documentation isn't very clear. Also, the on-premise version of the solution is less stable than the cloud version. In the next release, I'd like AWS CloudSearch to include a Python-based library improvement to communicate with other services and support for more languages.

I've been using AWS CloudSearch for about two years.

The cloud version of AWS CloudSearch is the most stable.

AWS CloudSearch is easy to scale.

Amazon's technical support needs to improve as they only solve about half our problems. 

Negative

AWS CloudSearch is easy to deploy.

We used an in-house team.

Our license costs around $4,000 per month.

We're switching to Microsoft Azure because customers in Europe prefer it due to their GDPR laws. I would rate AWS CloudSearch three out of ten.

I am using Amazon AWS CloudSearch for the s upfront application storage, and to install applications in the cloud for users to operate.

The most valuable feature of Amazon AWS CloudSearch is the cloud aspect. I do not need to have the physical infrastructure, everything is in the cloud.

I have been using Amazon AWS CloudSearch for approximately one year.

Amazon AWS CloudSearch is highly stable. However, the speed depends on your internet connection.

The scalability of Amazon AWS CloudSearch is good.

We have 10 people in my organization that use this solution. We do not plan to increase usage.

The support from Amazon AWS CloudSearch is satisfactory.

I have only used this solution.

The initial installation of Amazon AWS CloudSearch is easy. The time it took to complete the implementation was 10 minutes.

I did the implementation of the solution myself.

There was no license needed to use this solution.

I would recommend this solution to others.

I rate Amazon AWS CloudSearch an eight out of ten.

The best feature is its scalability in that Cloud is always on the fly. You can scale your requirements on the fly. Cloud also has other features but scalability comes first. This is one of the best features.

I think AWS is doing a good job. I don't think it needs much improvement. Security is a concern but they're working on it. I am not saying there is no security, but maybe they can bring in more controls.

I've been using AWS CloudSearch for three months.

The stability of the product is good.

As I mentioned, its scalability is its best feature.

We had a team of 15 - 20 people using it.

In terms of support, it's good - it's a market leader. Most of the issues are documented, so you really don't need support except for out of the ordinary stuff.

The initial setup is simple.

I'd definitely recommend Amazon AWS CloudSearch. On a scale of one to ten I'd rate it an eight.

We have multiple teams in our organization that use the solution.

There are plenty of services from the database. There are many features that are valuable.

Scalability and agility are good.

The pricing is okay.

The quality of the solution is good.

The solution delivers well on optimization.

In terms of customization, it's quite good and can work with any other cloud platforms.

I don't have a deep knowledge of the solution and its compatibility, so I don't know if I can speak to what might be lacking.

Scalability and agility could be improved slightly, even though we find them good right now.

The solution should improve the recovery aspects that it has on offer.

I've been using the solution for two to three years now.

We also use Azure.

Since my role is restricted to security protocols, I don't have too much information on the deployment and implementation of this solution.

The solution is very cost-effective.

My role and responsibility is to check the services of the security platform in question to see if it fits the requirements. For example, there are members of our team who are looking to leverage some services from the public cloud, I just look at their business requirements and see what services they want to leverage on a solution.

Physically if there is something that is lacking in security that I can foresee, I explain the best practices to follow to enable additional security controls. This may be making stronger authentications, authorizations, or having stronger data security and encryption. 

I'd rate the solution nine out of ten.

Depending on an organization's requirements and budgets, cloud services would be recommended. A user must just decide what they need and stick to one thing.