Atlas-DB vs Apache Drill: What are the differences?
Developers describe Atlas-DB as "Backend for managing dimensional time series data, by Netflix". Atlas was developed by Netflix to manage dimensional time series data for near real-time operational insight. Atlas features in-memory data storage, allowing it to gather and report very large numbers of metrics, very quickly. On the other hand, Apache Drill is detailed as "Schema-Free SQL Query Engine for Hadoop and NoSQL". Apache Drill is a distributed MPP query layer that supports SQL and alternative query languages against NoSQL and Hadoop data storage systems. It was inspired in part by Google's Dremel.
Atlas-DB and Apache Drill can be categorized as "Database" tools.
Some of the features offered by Atlas-DB are:
- Manages dimensional time series data
- In-memory data storage
- Captures operational intelligence
On the other hand, Apache Drill provides the following key features:
- Low-latency SQL queries
- Dynamic queries on self-describing data in files (such as JSON, Parquet, text) and MapR-DB/HBase tables, without requiring metadata definitions in the Hive metastore.
- ANSI SQL
Atlas-DB is an open source tool with 2.4K GitHub stars and 204 GitHub forks. Here's a link to Atlas-DB's open source repository on GitHub.