In this blog, we will see Data Analytical Stores
- Data warehouse
It is a relational database, stores data in schema.
Data from transactional store is transformed into schema where number value are stores in tables.
SQL queries are used.
- Data Lakes
A file store on distributed file system for high performance data access.
For structured or unstructured and semi structured data.
- Hybrid approach
Lake database or data lake house. Raw data is stored as file in data lake. Relational data abstracts these files and expose these as tables.
These tables can be queried with SQL, Azure Synapse analytics allow this.
- Azure synapse analytics
It bring together high performance SQL server based data warehouse with flexibility with flexibility of data lake.
Supports log and telementary analytics, data pipelines built in. For single unified analytics solution.
- Azure databricks
It is azure implementation of databricks platform.
Data bricks is built over apache spark, offers SQL and spark cluster.
Provides interactive UI to manage data in interactive notebooks
- Azure HDInsight
Better when migrating existing on premise Hadoop based solution to cloud.
Supports more than one open source analytics cluster types.
It's UI is not that good.
Thanks for reading <3