RTM Pro Verified Customer Reviews (2026)

DbVisualizer is a universal database management solution that helps organizations of all sizes work efficiently with relational and NoSQL databases. Built for developers, DBAs, analysts, and data engineers, it scales from startups to teams managing complex environments. The platform combines a SQL editor with autocomplete, visual query builders, and execution tools for database development and querying. An AI Assistant resolves errors and explains code, while built-in Git integration supports version control and collaboration. Teams can customize layouts, key bindings, and UI themes, mark frequent scripts and objects as favorites, and apply configurable security settings to meet compliance requirements. DbVisualizer connects to major databases including MySQL, PostgreSQL, SQL Server, Oracle, Snowflake, SQLite, Cassandra, and BigQuery, and runs on Windows, macOS, and Linux. With nearly 7 million downloads and Pro users in 150 countries, it's a proven fit for businesses of any size.

BigQuery serves as a serverless, multicloud data warehouse that simplifies the handling of diverse data types, allowing businesses to quickly extract significant insights. As an integral part of Google’s data cloud, it facilitates seamless data integration, cost-effective and secure scaling of analytics capabilities, and features built-in business intelligence for disseminating comprehensive data insights. With an easy-to-use SQL interface, it also supports the training and deployment of machine learning models, promoting data-driven decision-making throughout organizations. Its strong performance capabilities ensure that enterprises can manage escalating data volumes with ease, adapting to the demands of expanding businesses. Furthermore, Gemini within BigQuery introduces AI-driven tools that bolster collaboration and enhance productivity, offering features like code recommendations, visual data preparation, and smart suggestions designed to boost efficiency and reduce expenses. The platform provides a unified environment that includes SQL, a notebook, and a natural language-based canvas interface, making it accessible to data professionals across various skill sets. This integrated workspace not only streamlines the entire analytics process but also empowers teams to accelerate their workflows and improve overall effectiveness. Consequently, organizations can leverage these advanced tools to stay competitive in an ever-evolving data landscape.

SPC for Excel is a straightforward yet robust software package designed to meet all your needs for statistical process control and analysis. This tool empowers users to pinpoint areas of concern, derive insights from their data, detect emerging trends, and address issues—all within the familiar Excel environment. Whether you're a beginner or an expert, SPC for Excel supports your continuous improvement initiatives across various sectors, be they for-profit or non-profit organizations. It offers a comprehensive range of techniques for effective charting and analysis, including Pareto diagrams, histograms, control charts, Gage R&R assessments, process capability evaluations, distribution fitting, data transformation, regression analysis, design of experiments (DOE), hypothesis testing, and much more. With a one-time purchase, the software is yours indefinitely, allowing for two downloads per user and complimentary technical support. You can even explore a demo version to experience its ease of use firsthand. The software includes tools for process capability analysis to ensure customer satisfaction. Control charts and histograms help in the effective management of processes. Gage R&R studies validate your measurement systems, while problem-solving tools such as Pareto charts, scatter plots, and others assist teams in tackling challenges. Additionally, advanced data analysis features like DOE, ANOVA, and various statistical tests are available to cater to your more complex analytical needs. Ultimately, SPC for Excel stands as a versatile solution for those seeking to enhance their data analysis capabilities.