Bulk loading is the process where large volumes of data are loaded quickly and seamlessly into a database. It allows the import and export of data from one location to another much faster than conventional data loading methods. On cloud platforms, bulk loading typically involves the use of multiple nodes and parallelization to quicken the process.

What speeds up the process of data transfer through bulk loading? The database indexes used by most organizations are configured for inserting rows one at a time. This is time-consuming work when a lot of data have to be loaded all at once. On the other hand, bulk loading operations do not require data to be loaded one row at a time but employ a range of more efficient ways depending on the architecture of the database.

Often, transactional integrity is an issue with bulk loading as transactions are generally not logged. It also sometimes bypasses triggers and integrity checks. However, skirting these slow processes significantly enhances data loading performance and data loading time.

Visualize bulk loading as a way to transfer data into a database in big chunks. An example will explain this method better. Think that an organization has to enter all details of purchase transactions over a certain period into its database. In traditional data entry systems, this data would have been entered one order at a time. But if bulk loading methods are used all files with similar information – often hundreds of thousands of records – would be loaded into databases in a very short time.

Bulk loading is often referred to as bulk insert. This term was first used in the context of SQL Server databases but the principle is the same when used for other databases. Database administrators refer to SQL Bulk Insert when replicating huge volumes of SQL Server data and Oracle Bulk Insert when loading similar large volumes of Oracle data. However, all data warehouses and RDBMs have different outlooks to loading data and bulk loading may be carried out in a variety of ways based on the specific structure of the databases.

How does bulk loading work?

The flow operations of bulk loading are typically as follows.

•Extracting data from the source database

•Creating CSV, JSON, Avro, Parquet, or XML files in the staging area in one of the following - local file system, remote FTP or SFTP server, Azure Blob, Google Cloud Storage, or Amazon S3. The location of the staging area rests on the particular implementation of the bulk loading command for the destination database.

•Compressing files with the gzip algorithms.

•Checking to verify if a destination table is present, if not, creating the table with metadata from the source.

•Executing the user-specified SQL statements for bulk loading

•Optimally executing user-defined MERGE statements that are automatically generated.

•Finally, if required, cleaning the remaining files in staging.

This in a nutshell is bulk loading data into a database.