The goal of this project is to assess basic ways of storing time series data in Azure.
There are a number of companies that specialize in cloud-based time series data historians. For projects with extremely large storage requirements, high-performance needs, or advanced features such as model-based compression or interpolation, it's advisable to look at the existing products on the market.
These third-party solutions may be much easier to implement versus creating an in-house solution.
Click on a storage solution header for details.
SQL Database | Blob Storage | HBase | Azure Data Lake | OpenTSDB | |
---|---|---|---|---|---|
Writes | Excellent | Excellent | |||
Random Access Reads | Excellent | Poor | Poor | ||
Batch Reads | Excellent | Good | Excellent | ||
Aggregation | Good (TSQL) | Poor | Excellent | ||
Storage Efficiency | Excellent | Excellent | Excellent | ||
Cost | Configurable | Excellent | |||
Interpolation | Excellent | ||||
Interoperability | Excellent | Poor |
- DocumentDB