About

Parqify - our flagship product.

We're a team of Big Data specialists with 20+ years of hands-on consulting experience across industries.

In our client engagements, we consistently saw customers landing data on Amazon S3 in JSON or CSV file formats.

The appeal was obvious: nearly every ETL/ELT tool and SaaS platform supports these formats, making them practical, interchangeable raw-zone options with schema-on-read flexibility.

They also matched common data producers—application logs, CDC feeds, IoT events, and clickstreams—which are often emitted as JSONL or delimited text and easily written directly to S3. Operationally, CSV and JSON are human-readable, which speeds up debugging and ad-hoc inspection.

We found that converting these files to Parquet consistently delivered clear advantages for long-term archiving and analytics—improving performance, cost efficiency, and reliability.

Parquet's columnar compression reduced S3 storage footprint by multiples compared to CSV/JSON, and a date-based partitioning scheme (year/month/day) made it straightforward to tier older partitions and read only the slices needed—lowering both storage and access costs.

Across customers, we observed a gap: teams lacked a fast, dependable way to convert CSV/JSON files on S3 to Parquet with the right combination of speed, compression, schema guarantees, and optimization.

We designed a solution to fill that gap—and plan to offer it on the AWS Marketplace as a click-to-deploy product.