I first used Aiven Platform five years ago when I was in college for various projects, which included using SQL for my RAG bots and SQL for a finance analysis tool. Last year, I also used it for SQL databases and tools.

My main use case for Aiven Platform currently is the SQL database, as I use Aiven Platform's SQL hosted database for my MVPs, such as RAG tools, finance analyzers, archaeology chatbots, or other MVPs which include the usage of SQL databases.

My first MVP was built using Aiven Platform and Tesseract OCR. In this project, I asked users to upload their passbook, which was completely encrypted and never stored in any database. Once uploaded, the AI analyzed the passbook data against pre-configured settings to suggest products based on their spending behavior, specifically using SQL to analyze the data with pre-configured data stored on Aiven Platform.

In addition to my previous projects, I used Aiven Platform for building another MVP, specifically a pipeline for image classification where I built an integrity checks tool that can run a batch job on the cloud. This allows me to analyze hundreds and thousands of images and store results on whether the person is cheating or not.

The features I like about Aiven Platform include the cloud platform and the database hosting. One of my favorite features is SQL hosting, which is provided by very limited platforms, offering free SQL hosting that is more than sufficient for my MVPs and significantly aids in building products around SQL.

The performance of Aiven Platform is quite good, as I have not seen any downtime, and it is very reliable, with backups in place, allowing me to fetch data without experiencing any high latency, even as a free tier user.

Many workflows, including integrity pipelines, are positively impacted by Aiven Platform, which is also very cost-efficient, making it beneficial for my projects.

I would appreciate more documentation of workflows in Aiven Platform, such as details on Cloud jobs and GCP buckets, since having additional resources would be beneficial.

If Aiven Platform provides enhanced documentation, it will address many needs. While I have not faced any friction with the UI, slight improvements regarding integration guidance would be great.

I have been working as a software engineer for around two years, focusing on systems more on React and web solutions.

Aiven Platform is stable, and I have not experienced any downtime throughout my usage.

The scalability of Aiven Platform is very good for my use case, especially when creating minimal viable products, as it effectively handles scalability issues.

Customer support for Aiven Platform is not needed frequently, but if I encounter any issues such as losing data or query problems, support is available.

Previously, I was using DigitalOcean and Heroku cloud solutions, but I switched to Aiven Platform because of its continuous maintainability, improvement, and SQL support, which I appreciated the most.

I have faced no issues with Aiven Platform's pricing, setup cost, and licensing, as it is easy to manage.

I achieved a 70% boost in cost-cutting, and with improvements to the setup process, we can benefit from fewer employees required for setup work.

Regarding cost-efficiency, using Aiven Platform allows me to store a JSON payload of around 10,000 lines for evaluation results, making it reliable and optimized. This reduced costs to 30 rupees compared to 100 rupees previously with other providers, resulting in a 70% cost efficiency.

I evaluated other options before choosing Aiven Platform, including AWS solutions and Heroku, but the benefits I gained from Aiven are much more superior.

My advice to others looking into using Aiven Platform is to focus on leveraging it for more database integration work, as reliability and cost-effectiveness are compelling reasons to adopt the platform.

I have been using Aiven Platform for the last five years and have recommended it to people in my organization for creating minimal viable products and prototypes before building actual solutions. I really appreciate the platform. I would rate this review as 7.5 out of 10.

Our primary use case is having our PostgreSQL and MySQL databases hosted by Aiven Platform. They serve as our production databases.

One of the most valuable features of Aiven Platform is that it handles the upgrades for us seamlessly, saving us time that would be spent on routine upgrades. It also provides reliable backups. The ability to minimize disruption during upgrades is very important since any database downtime would mean system-wide disruptions.

I would really like to see Aiven Platform add a user interface for database backups, as this would eliminate the need for a third-party solution. Additionally, the customer service could be more responsive to regain my trust as it felt inefficient in the past.

I have been using Aiven Platform for eight years.

Customer service usually responds promptly, but there have been times when communication felt like throwing an inquiry over a wall and waiting for a reply. It detracted from getting a quick understanding and solution for challenges.

We used Engine Yard's support for databases before switching to Aiven Platform. Every upgrade was a hassle and nerve-wracking. We by usign Aiven we needed fewer servers because of we did need serves to hodt the PG and MySql databases.

The cost for hosting with Aiven Platform seems high compared to managing it ourselves.

In our experience, we encountered issues with Aiven Platform's connection to Redis. It was not smooth, and though we like the solution overall, we are hesitant about using Redis integration again. Additionally, on a scale of one to ten, I would rate Aiven Platform a nine due to the alck of an interface for backups and a more responsive customer service.

I use Aiven for Apache Kafka to handle services dependent on each other. Instead of API calls, we use it for asynchronous processing of all our services. That's the general way we use it.

What I like best about the tool is that the process for the services is faster compared to other methods. It's easier to use because Aiven for Apache Kafka handles the maintenance, so we have less to manage. We only use Kafka to manage its connectivity.

One challenge we face is when we want to update the version, for example, from 3.6 to 3.7. It will spawn new nodes, and then there's rebalancing and syncing from other brokers. There's high CPU usage during this process, so the solution can't be used for a while, causing some downtime in our services. To tackle this challenge, we schedule maintenance updates during low-traffic periods when there's less risk and fewer users use the services.

I have been using the product since 2020.

I think scalability is quite challenging. When we upgrade the machine or disk or change the machine nodes, the new node needs to rebalance and sync with other brokers. This causes high CPU usage and disrupts Aiven for Apache Kafka and all our services. That's the main challenge for scalability. I'd rate the scalability around seven or eight out of ten, as long as you know the strategy for scaling.

We haven't had any significant issues so far. Our manager can escalate issues to the solution's engineers even when we have issues. They provide a fast response to our incidents and solve our issues. After solving the problem, the engineers also look into the issue to find the root cause.

We've contacted their support before. We submit support tickets and follow up with our account manager. The account manager can then follow up with the engineers, which helps the ticket get processed faster.

Their support team has several experts, especially in Apache Kafka. We can always ask them about specific issues. For example, our principal engineer once asked about Kafka offset, and the account manager was able to handle it and provide best practices.

The tool's deployment is easy. We choose the VPC, the region, and whether we use the solution's VPC or our own. We select the version and the plan (basic or business), create the service, and it is ready to use after a few minutes. That's one of the best things about deploying it.

For security, our services use the solution's default authorization. We have to authenticate and use either SASL or a keystore file for authorization. This ensures that anyone outside our network can't access the topics.

Apache Kafka is really good for streaming data or messaging services. It's comparable to other messaging services.

Overall, I'd rate Aiven for Apache Kafka an eight out of ten.