CloudBeaver AWS can be improved because in rendering of the queries, if it is very complex or big, the responses in the browser get slowed down. Compared to DBeaver of desktop, it is noticeably very slower on the browser of AWS and heavy data engineering can be done, but it will have very slow responses configured altogether. That needs to be maintained. Even there is no connectivity of machine learning, MLflow kind of thing where Airflow or PySpark approaches can be integrated. Python pipelines can be created but the whole end-to-end machine learning pipeline gets stuck whenever we work out with DBeaver. That again is one of the issues that I would look out for to improve. Also, I need to maintain the infrastructure perfectly here. I need to manage it and need to identify the risks as well. The whole proper setup of VPCs or IAMs needs to be done. It is not a NLQ kind of thing. User queries need to be configured in manual approaches, not automated currently. It should be automated now. Debugging is very painful. That again is a vague approach here. Errors can be executed and we will not be getting out the clarity as well. During this whole approach, the logs are not perfect and intuitive and debugging is also very limited. The user interface and documentation look good, but I would still suggest improvements.
DevOps engineer at a tech services company with 51-200 employees
Real User
Top 20
Jan 5, 2026
While CloudBeaver AWS meets most of our needs, there are a few areas where it could be improved. Enhanced support for more advanced query visualization and analytics features would be useful for our data teams. Performance optimization for very large datasets could also help. More granular auditing and alerting features would strengthen the security perspective. In terms of security, I can improve more of the features of CloudBeaver AWS. I could bring in encryption functionality and also store the database credentials in the AWS Secret Manager to integrate it with more AWS services. An additional area that could be improved is the user interface for managing multiple databases, including a more streamlined interface for managing multiple connections, better handling of long-running queries, and deeper integration with AWS services and other services to support larger teams with complex workflows. Instead of manually installing CloudBeaver AWS, I could directly attach it to the CI/CD pipeline. That would increase productivity. I could easily and directly connect the database endpoint to CloudBeaver AWS, which would be a more time-saving method, rather than manually going to the CloudBeaver AWS console and entering each database endpoint, username, password, and database name. In addition, it would be valuable if I could combine the AWS SSM Manager with CloudBeaver AWS to connect easily using localhost. That would be beneficial for configuring a bastion host. Some environments, companies, or organizations prefer using a bastion host over a VPN, so for them, that would be a great addition.
Database Management Systems efficiently store, retrieve, and manage data for various applications. They provide reliable solutions for structured and unstructured data, ensuring privacy and integrity.Modern Database Management Systems are designed to simplify data management tasks while offering robust functionalities that support both transactional and analytical applications. Their adaptability across industries has been driven by the increasing demand for scalable, secure data solutions....
CloudBeaver AWS can be improved because in rendering of the queries, if it is very complex or big, the responses in the browser get slowed down. Compared to DBeaver of desktop, it is noticeably very slower on the browser of AWS and heavy data engineering can be done, but it will have very slow responses configured altogether. That needs to be maintained. Even there is no connectivity of machine learning, MLflow kind of thing where Airflow or PySpark approaches can be integrated. Python pipelines can be created but the whole end-to-end machine learning pipeline gets stuck whenever we work out with DBeaver. That again is one of the issues that I would look out for to improve. Also, I need to maintain the infrastructure perfectly here. I need to manage it and need to identify the risks as well. The whole proper setup of VPCs or IAMs needs to be done. It is not a NLQ kind of thing. User queries need to be configured in manual approaches, not automated currently. It should be automated now. Debugging is very painful. That again is a vague approach here. Errors can be executed and we will not be getting out the clarity as well. During this whole approach, the logs are not perfect and intuitive and debugging is also very limited. The user interface and documentation look good, but I would still suggest improvements.
While CloudBeaver AWS meets most of our needs, there are a few areas where it could be improved. Enhanced support for more advanced query visualization and analytics features would be useful for our data teams. Performance optimization for very large datasets could also help. More granular auditing and alerting features would strengthen the security perspective. In terms of security, I can improve more of the features of CloudBeaver AWS. I could bring in encryption functionality and also store the database credentials in the AWS Secret Manager to integrate it with more AWS services. An additional area that could be improved is the user interface for managing multiple databases, including a more streamlined interface for managing multiple connections, better handling of long-running queries, and deeper integration with AWS services and other services to support larger teams with complex workflows. Instead of manually installing CloudBeaver AWS, I could directly attach it to the CI/CD pipeline. That would increase productivity. I could easily and directly connect the database endpoint to CloudBeaver AWS, which would be a more time-saving method, rather than manually going to the CloudBeaver AWS console and entering each database endpoint, username, password, and database name. In addition, it would be valuable if I could combine the AWS SSM Manager with CloudBeaver AWS to connect easily using localhost. That would be beneficial for configuring a bastion host. Some environments, companies, or organizations prefer using a bastion host over a VPN, so for them, that would be a great addition.