Data Mesh: An Executive Guide to Modern Data Architecture in Manufacturing

This page summarizes the projects mentioned and recommended in the original post on dev.to

InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
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SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
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  • solid

    Solid - Re-decentralizing the web (project directory) (by solid)

    As Data Mesh gains traction, specialized tools, and platforms are evolving to support its principles and practices. These tools will enhance data product development capabilities, self-serve infrastructure, and federated governance, making it easier for organizations to implement and maintain Data Mesh. SolidProject, for example, provides tools for creating decentralized data pods that allow users to own and control their data. This aligns with Data Mesh principles by enabling domain-specific data ownership and promoting data privacy and security. Solid's framework allows for interoperability between different data systems while maintaining user control over data, which is crucial for the distributed nature of Data Mesh architectures (SolidProject, 2024).

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • kubernetes

    Production-Grade Container Scheduling and Management

    A manufacturing company might leverage a combination of Kafka for real-time data streaming, Kubernetes for container orchestration, and dbt for data transformations. They could use Dataplex for unified data management and security across domains. This technology stack would enable the Production Data team to monitor and analyze production metrics in real-time, the Supply Chain Data team to manage and optimize logistics and inventory, and the Quality Control Data team to ensure product compliance and quality. By investing in these tools, the company can effectively support the decentralized data management and governance principles of Data Mesh.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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