The 3 Most Popular Data Engineering Tools are MongoDB, Tableau, and Kubernetes, New Study by Dattell Finds

The 5 most popular data engineering tools are MongoDB, Tableau, Kubernetes, PostgreSQL, and Ansible, according to a new industry study by Dattell.

The study also looked at job data to determine which specialties are in highest demand by employers and which ones have the highest salaries.

The study was conducted by collecting 3.5 billion data points to assess the popularity of 59 data engineering tools that fell into the following categories:  Data Processing, Data Orchestration, Data Storage, Data Visualization, and Languages/Libraries. A full research methods document is linked in the report.

Recommended AI News: Huobi Global Unveils Blockchain Ecosystem Investment Arm Ivy Blocks to Spur Industry Development

The major findings uncovered by the study include:

5 most popular technologies. The most popular technologies are MongoDB, Tableau, Kubernetes, PostgreSQL, and Ansible.

340,000 Job Openings. There are over 340,000 open data engineering jobs.

Kubernetes highest paying specialty. There is a 3-fold range of salaries for data engineering jobs, with Kubernetes paying the highest, with salaries reaching $180,000, and Tableau paying the lowest.

Companies opting for free data processing tools. Free data processing tools are preferred 62% of the time, over paid alternatives.

Industry split on whether to pay for data storage. Data engineers are split on whether to pay for data storage tools, with the top four storage tools being an equal mix of paid and free tools.

Python most important language. Python is the most popular programming language, followed by Java and SQL.

Clear winners in the data orchestration space. Kubernetes and Ansible control 65% of the data orchestration space.

Companies preferring to pay for data visualization tools. The top 10 data visualization tools are all paid tools.

Recommended AI News: Ooredoo Selects Icertis Contract Intelligence as Part of Enterprise Digital Transformation

[To share your insights with us, please write to sghosh@martechseries.com]