BigTable is a distributed database that was developed by Google to handle massive amounts of structured data. It is used by various Google services such as Google Search, Google Maps, and Google Analytics. The data model of BigTable is a sparse, distributed, persistent multidimensional sorted map. Here is a brief explanation of the structure of the BigTable data model:
Tables: BigTable stores data in tables, which are similar to tables in a relational database. A table consists of a set of rows, each of which is uniquely identified by a row key.
Column Families: Each row in a BigTable table can have multiple column families, which are groups of related columns. Column families are defined when a table is created and cannot be changed later. All columns in a column family have the same prefix and are stored together on disk.
Columns: Columns are the basic unit of data storage in BigTable. Each column has a unique name that is specified as a combination of a column family name and a qualifier. Column qualifiers are used to distinguish between different columns within a column family.
Timestamps: BigTable allows multiple versions of a cell to be stored, each with a different timestamp. Timestamps are used to support versioning of data, allowing users to retrieve historical versions of a cell.
Cells: A cell is the intersection of a row, column, and timestamp. It contains a piece of data, which can be of any type, such as a string, integer, or binary data.
Tablet: BigTable splits each table into smaller pieces called tablets, which are distributed across multiple servers in the cluster. Tablets are used to enable scalability and fault-tolerance.
The structure of the BigTable data model is designed to provide efficient and scalable storage and retrieval of large amounts of structured data. By using a sparse, distributed, persistent multidimensional sorted map, BigTable is able to handle massive amounts of data and provide fast and efficient access to that data.
