Data Platform Vendor Agnostic

Assumptions about Platform/Vendor Agnostic standards, structures, tools, and languages:

  1. Open standard formats, structures, tools, and languages are better than proprietary vendor specific formats, structures, tools, and languages.
  2. The ability to move data, code, workflows, processes, and solutions between vendors and platforms without re-architecting or lengthy migration efforts provides the flexibility needed to consider and change vendors based on cost, performance, and security as needed when the current vendor relationship becomes untenable.  Clients who are Platform/Vendor agnostic are in a strong position when negotiating with vendors because the barriers that typically inhibit changing vendors have been reduced or eliminated.
  3. Open Source Tools, Code, and File Formats like R, RStudio, Python, Spark, PrestoDB, Trino, ANSI SQL, HIVE, Avro, ORC, Parquet, SCALA, OpenJDK JAVA, Delta Lake, PyTorch, mlflow, TensorFlow, and Apache Superset
Scroll to Top