Columnar efficiency
Parquet is designed for analytical processing, making it a better fit for workloads that benefit from column-oriented storage and selective reads.
GeoIP Parquet downloads
GeoIP Parquet downloads for analytics pipelines and larger-scale processing.
Parquet is the stronger option when GeoIP data needs to be processed in analytics workflows, batch jobs, or columnar engines. ProdIPData publishes Parquet release indexes so users can browse the current monthly packages and work from a structured snapshot built for reuse.
Open the current Parquet release index, compare it with the CSV guide, or return to the downloads hub for the full release view.
Batch and pipeline friendly
Use Parquet when the goal is to move GeoIP data into Python, notebooks, data lake workflows, or other repeatable analytical pipelines.
Release-oriented comparisons
Monthly release labels make it easier to compare snapshots over time and keep analytical outputs tied to a known version of the published data.
When Parquet is usually the right choice
- Analytics-heavy workflows that need a more efficient file format than plain CSV.
- Processing paths where country and topic packages are consumed in code rather than manually reviewed line by line.
- Teams that already work in Python, notebook, or data-processing ecosystems that understand Parquet well.
Where to go next
- Open the current Parquet release index to browse published package links and topic coverage.
- Use the coverage page when you want to narrow the country focus before downloading files.
- Use the CSV guide if operational readability matters more than analytical efficiency.
GeoIP database overview
See where Parquet sits in the broader GeoIP product and release model.
IP geolocation data
Read the interpretation guide if the main question is what the data means rather than how to process it.
Release methodology
Understand the monthly publication cadence that supports Parquet release comparison.