Best Data Visualization Software for Kubernetes

Turn your customers into success stories with built-in intelligence featuring state of the art analytics, dashboards and more. Bold BI is a platform designed from the ground up to be embedded, there are no compromises, no shortcuts. Outdated requirements such as “bring all your data into our data store or cube” today add unnecessary complexity to your application. With some solutions, you must design a complex system for data integration and keep the embedded BI data store in sync with your data sources. With Bold BI, you connect directly to hundreds of data sources and any data warehouse of your choice. Deploy with single-tenant mode if you have a shared data model. If you have an isolated data model, use multi-tenant mode to maintain a single source for dashboards and publish across different tenants. Bold BI is designed to accommodate scenarios common and uncommon. Embed Bold BI directly from your application code using powerful JavaScript APIs.

AllegroGraph is a breakthrough solution that allows infinite data integration through a patented approach unifying all data and siloed knowledge into an Entity-Event Knowledge Graph solution that can support massive big data analytics. AllegroGraph utilizes unique federated sharding capabilities that drive 360-degree insights and enable complex reasoning across a distributed Knowledge Graph. AllegroGraph provides users with an integrated version of Gruff, a unique browser-based graph visualization software tool for exploring and discovering connections within enterprise Knowledge Graphs. Franz’s Knowledge Graph Solution includes both technology and services for building industrial strength Entity-Event Knowledge Graphs based on best-of-class tools, products, knowledge, skills and experience.

Monitor your data health and pipeline performance. Gain unified visibility for pipelines running on cloud-native tools like Apache Airflow, Apache Spark, Snowflake, BigQuery, and Kubernetes. An observability platform purpose built for Data Engineers. Data engineering is only getting more challenging as demands from business stakeholders grow. Databand can help you catch up. More pipelines, more complexity. Data engineers are working with more complex infrastructure than ever and pushing higher speeds of release. It’s harder to understand why a process has failed, why it’s running late, and how changes affect the quality of data outputs. Data consumers are frustrated with inconsistent results, model performance, and delays in data delivery. Not knowing exactly what data is being delivered, or precisely where failures are coming from, leads to persistent lack of trust. Pipeline logs, errors, and data quality metrics are captured and stored in independent, isolated systems.