Overall Satisfaction with Apache Spark
It's being replaced as the traditional ETL tool and we are using Apache Spark for data science solutions.
- It makes the ETL process very simple when compared to SQL SERVER and MYSQL ETL tools.
- It's very fast and has many machine learning algorithms which can be used for data science problems.
- It is easily implemented on a cloud cluster.
- The initialization and spark context procedures.
- Running applications on a cluster is not well documented anywhere, some applications are hard to debug.
- Debugging and Testing are sometimes time-consuming.
- Time saved in developing applications is less.
- ROI on time, resources, money.
- Can replace the traditional database systems.
Evaluating Apache Spark and Competitors
Yes - Microsoft Server
- Price
- Product Features
- Product Usability
- Product Reputation
- Prior Experience with the Product
- Vendor Reputation
- Existing Relationship with the Vendor
- Analyst Reports
It works on all kinds of data unlike SQL Server which needs structured data.
I would think ofROI and resource allocation as the most important factors.