File geodatabases: compressing vs. compacting
Although conceptually similar in that each can result in more compact storage, compressing and compacting as applied to file geodatabases are two unrelated operations.
First, the term compression is used in various ways, and file geodatabase compression is not to be confused with these other unrelated types of compression:
- The ArcCatalog Compress command, which removes unused version data from an ArcSDE geodatabase
- Raster compression: JPEG, JPEG 2000, or LZ77 compression schemes
- WinZIP compression, the popular generic compression utility
File geodatabase compression is, however, related to Smart Data Compression (SDC); it applies the same underlying technique and offers comparable benefits.
What is file geodatabase compression?
To reduce storage requirements, you can compress vector file geodatabase feature classes and tables to a read-only format. Once compressed, a dataset looks the same in ArcCatalog and ArcMap as when it was uncompressed. Also, apart from editing, you work with it the same way. The compressed data is a direct-access format, so you do not have to decompress it each time you access it; ArcGIS and ArcReader read it directly.
You might think of compression as squeezing, squashing, or crunching data, but this is not what happens when you compress data. Compression does not physically cram data into a smaller space. Instead, it reencodes it into a different, more compact pattern. The result is usually smaller than the original because the compression process removes redundancy from the data.
For example, the run of three A41s
A41 A41 A41
can be reencoded to the following:
A41(3)
The (3) indicates A41 repeats three times. To display the compressed data, ArcGIS reinterprets A41(3) back into A41 A41 A41. This is just one strategy ArcGIS uses to compress file geodatabase data. ArcGIS applies different strategies for different fields, depending on the type of data, the number of unique values, and how often values repeat.
The amount of compression possible for a given dataset depends on several factors, but the type of features and the amount of redundancy in attribute data are the most important. For more information, see About compressing file geodatabase data.
What is compacting?
Compacting tidies up storage of records in files by reordering them and eliminating empty space. If you frequently add and delete data in a file or personal geodatabase, you should compact your geodatabase on a monthly basis. This can reduce file sizes and improve performance. Compacting uncompressed data is unrelated to file geodatabase compression and therefore should be considered independently. For more information, see Compacting file and personal geodatabases.