Jaspersoft vs. myDBR Comparison Chart

Dashboards, codeless reporting, interactive data visualizations, data level security, mobile access, scheduled reports, embedding, sharing via link, and more. DashboardFox is a dashboard and data visualization solution designed for business users with a no-subscription pricing model. Pay once and you own the software for life. DashboardFox is self-hosted, install on your own server, behind your firewall. Looking for Cloud BI? We offer managed hosting services, but you still retain ownership of your DashboardFox licenses and data. DashboardFox allows your users to drill-down and interact with live data visualizations via dashboards and reports. Business users can create new visualization in a codeless report builder without needing a technical pedigree. An alternative to Tableau, Sisense, Looker, Domo, Qlik, Crystal Reports, and others.

Researching Reporting Software? Welcome to Yurbi. Convert your data into real-time reports and dashboards. Reporting software designed for business users, but with robust security to protect your data. Speak to a technical expert (not a high pressured sales call) by filling out the form on this page so we can schedule a meeting or demo and discuss if Yurbi is a good fit or not. Yurbi is a reporting solution designed for business users with a flat-based, transparent pricing model. Yurbi allows your users to have self-service access to live data business reports and dashboards with limited technical help. Enterprise features such as data security keep your data protected. Self-hosted reporting software at a fraction of the cost of comparable options. An alternative to Tableau, Looker, Sisense, Board, Phocas, and other leading database reporting tools.

dbt helps data teams transform raw data into trusted, analysis-ready datasets faster. With dbt, data analysts and data engineers can collaborate on version-controlled SQL models, enforce testing and documentation standards, lean on detailed metadata to troubleshoot and optimize pipelines, and deploy transformations reliably at scale. Built on modern software engineering best practices, dbt brings transparency and governance to every step of the data transformation workflow. Thousands of companies, from startups to Fortune 500 enterprises, rely on dbt to improve data quality and trust as well as drive efficiencies and reduce costs as they deliver AI-ready data across their organization. Whether you’re scaling data operations or just getting started, dbt empowers your team to move from raw data to actionable analytics with confidence.

BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven. Gemini in BigQuery offers AI-driven tools for assistance and collaboration, such as code suggestions, visual data preparation, and smart recommendations designed to boost efficiency and reduce costs. BigQuery delivers an integrated platform featuring SQL, a notebook, and a natural language-based canvas interface, catering to data professionals with varying coding expertise. This unified workspace streamlines the entire analytics process.

Align analytics to your everyday business workflows. Your business relies on people, data and documents, but the process of using them is broken. QuaerisAI enables seamless downstream workflows across your People, Documents and Data Assets. Use natural language search on data, documents and collaborate in private or within Communities - all in one platform! QuaerisAI offers time savings of at-least 30 minutes to an hour/day/resource - imagine the productivity enhancements you give your users without the expense of buying and consolidating a bunch of AI tools. Quaeris can be rolled out to team of 10s or 1000s of users seamlessly within a matter of days - without much need of IT, and that is why IT & data teams love us!

AnalyticsCreator is a metadata-driven data warehouse automation solution built specifically for teams working within the Microsoft data ecosystem. It helps organizations speed up the delivery of production-ready data products by automating the entire data engineering lifecycle—from ELT pipeline generation and dimensional modeling to historization and semantic model creation for platforms like Microsoft SQL Server, Azure Synapse Analytics, and Microsoft Fabric. By eliminating repetitive manual coding and reducing the need for multiple disconnected tools, AnalyticsCreator helps data teams reduce tool sprawl and enforce consistent modeling standards across projects. The solution includes built-in support for automated documentation, lineage tracking, schema evolution, and CI/CD integration with Azure DevOps and GitHub. Whether you’re working on data marts, data products, or full-scale enterprise data warehouses, AnalyticsCreator allows you to build faster, govern better, and deliver

ActiveBatch by Redwood makes setting up and launching automation easy with no custom scripting required. With a low-code Super REST API adapter, over 100 pre-built job steps and a user-friendly drag-and-drop workflow designer, you can integrate across any system, application and data source, on-prem, in the cloud or in hybrid environments. Maintain complete control and visibility and meet SLAs with monitoring of all automation from a single pane of glass and get custom alerts via emails or SMS. Managed Smart Queues dynamically scale resources for high-volume workloads, reducing process times while the self-service portal enables business users to run and monitor workflows independently. ActiveBatch meets security and compliance standards, with ISO 27001 and SOC 2, Type II certifications, encrypted connections and regular third-party tests, always keeping security at the forefront. Along with ongoing product advancements, get the added benefit of 24x7 support and on-site training.

Grafana Labs provides an open and composable observability stack built around Grafana, the leading open source technology for dashboards and visualization. Recognized as a 2025 Gartner® Magic Quadrant™ Leader for Observability Platforms and positioned furthest to the right for Completeness of Vision, Grafana Labs supports over 25M users and 5,000+ customers—including Bloomberg, Citigroup, Dell Technologies, Salesforce, and TomTom. The LGTM Stack combines Grafana for visualization, Mimir for metrics, Loki for logs, and Tempo for traces. Grafana Cloud, the fully managed offering, accelerates time to value with turnkey solutions for Kubernetes monitoring, incident response, load testing, and more. It features Adaptive Metrics for cost-efficient data aggregation and native OpenTelemetry support. Built on open standards, Grafana empowers teams to visualize and correlate data from any source—without vendor lock-in—whether self-managed or in the cloud. Grafana Cloud scales with you, securely.

Develop the automations that work for you. With ThinkAutomation, you get an open-ended studio to build any and every automated workflow you could ever need. All without volume limitations, and all without paying per process, license or ‘robot’.

Teradata VantageCloud: The complete cloud analytics and data platform for AI. Teradata VantageCloud is an enterprise-grade, cloud-native data and analytics platform that unifies data management, advanced analytics, and AI/ML capabilities in a single environment. Designed for scalability and flexibility, VantageCloud supports multi-cloud and hybrid deployments, enabling organizations to manage structured and semi-structured data across AWS, Azure, Google Cloud, and on-premises systems. It offers full ANSI SQL support, integrates with open-source tools like Python and R, and provides built-in governance for secure, trusted AI. VantageCloud empowers users to run complex queries, build data pipelines, and operationalize machine learning models—all while maintaining interoperability with modern data ecosystems.