Question 1

What are the best open-source data ingestion tools?

Accepted Answer

The list includes popular options like Apache Kafka for streaming, Airbyte for ELT, and Fluentd for logging, but it doesn't rank them—you'll need to evaluate based on your use case like real-time vs. batch processing.

Question 2

Apache Flink vs Apache Spark for stream processing?

Accepted Answer

Both are listed under Stream Processing, but the list doesn't compare them. Flink is noted for streaming dataflow, while Spark handles batch and streaming; research outside the list is needed for latency, scalability, and ecosystem differences.

Question 3

How to choose a workflow scheduler for data pipelines?

Accepted Answer

The list includes tools like Apache Airflow, Prefect, and Dagster, but it lacks guidance. Consider factors like code vs. UI preference, scaling needs, and integration with your existing stack, as each has different philosophies.

Question 4

Is this awesome list updated regularly for new data engineering tools?

Accepted Answer

It's community-maintained, so updates depend on contributors; while it has recent additions like Pathway and DataRaven, check the GitHub commit history for activity, as some sections might become outdated.

Question 5

What time-series databases are recommended for IoT?

Accepted Answer

The list covers options like InfluxDB, TimescaleDB, and QuestDB under Timeseries, but without recommendations. Evaluate based on write throughput, query performance, and cloud support for your specific IoT scale.

Data Engineering

What is Data Engineering?

Overview

Use Cases

Best For

Related Projects

Found a gem we're missing?

Not Ideal For

Pros & Cons

Pros

Cons

Frequently Asked Questions