Best Data Visualization Software for Docker

Find and compare the best Data Visualization software for Docker in 2024

Use the comparison tool below to compare the top Data Visualization software for Docker on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Deepnote Reviews
    Deepnote is building the best data science notebook for teams. Connect your data, explore and analyze it within the notebook with real-time collaboration and versioning. Share links to your projects with other analysts and data scientists on your team, or present your polished, published notebooks to end users and stakeholders. All of this is done through a powerful, browser-based UI that runs in the cloud.
  • 2
    Latitude Reviews
    Answer questions today, not next week. Latitude makes it easy to create low-code data apps within minutes. You don't need a data stack, but you can help your team answer data-related questions. Connect your data sources to Latitude and you can immediately start exploring your data. Latitude connects with your database, data warehouse, or other tools used by your team. Multiple sources can be used in the same analysis. We support over 100 data sources. Latitude offers a vast array of data sources that can be used by teams to explore and transform data. This includes using our AI SQL Assistant, visual programming, and manually writing SQL queries. Latitude combines data exploration with visualization. You can choose from tables or charts and add them to the canvas you are currently working on. Interactive views are easy to create because your canvas already knows how variables and transformations work together.
  • 3
    AllegroGraph Reviews
    AllegroGraph is a revolutionary solution that allows infinite data integration. It uses a patented approach that unifies all data and siloed information into an Entity Event Knowledge Graph solution that supports massive big data analytics. AllegroGraph uses unique federated sharding capabilities to drive 360-degree insights, and enable complex reasoning across a distributed Knowledge Graph. AllegroGraph offers users an integrated version Gruff, a browser-based graph visualization tool that allows you to explore and discover connections within enterprise Knowledge Graphs. Franz's Knowledge Graph Solution offers both technology and services to help build industrial strength Entity Event Knowledge Graphs. It is based on the best-of-class products, tools, knowledge, skills, and experience.
  • 4
    IBM Databand Reviews
    Monitor your data health, and monitor your pipeline performance. Get unified visibility for all pipelines that use cloud-native tools such as Apache Spark, Snowflake and BigQuery. A platform for Data Engineers that provides observability. Data engineering is becoming more complex as business stakeholders demand it. Databand can help you catch-up. More pipelines, more complexity. Data engineers are working with more complex infrastructure and pushing for faster release speeds. It is more difficult to understand why a process failed, why it is running late, and how changes impact the quality of data outputs. Data consumers are frustrated by inconsistent results, model performance, delays in data delivery, and other issues. A lack of transparency and trust in data delivery can lead to confusion about the exact source of the data. Pipeline logs, data quality metrics, and errors are all captured and stored in separate, isolated systems.
  • 5
    Elucidata Polly Reviews
    Polly allows you to harness the power of biomedical information. The Polly Platform allows you to scale batch jobs, workflows and visualization applications. Polly supports resource pooling, optimizes resource allocation based upon your usage requirements, and makes use of spot instances when possible. This results in optimization, efficiency, quicker response time, and lower costs for resources. Access a dashboard that allows you to monitor and track resource usage and costs in real-time. This will allow you to reduce overheads when resource management is done by your IT team. Polly's infrastructure is built around version control. Polly uses a combination dockers and interactive notebooks to ensure version control for your analyses and workflows. We have created a mechanism that allows data, code, and the environment to co-exist. This, along with cloud data storage and the ability for users to share projects, ensures reproducibility in every analysis.
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