Easy it is to use. Column-store data has many benefits. Review collected by and hosted on G2.com.

Learning curve. It took a while to figure it out, but once I did it was great. Review collected by and hosted on G2.com.

It is a widely adopted file format that works well with all big data applications. Review collected by and hosted on G2.com.

I have no complaints about parquet. It's just a file format, much like CSVs. I guess one complaint is that you have to re-write your parquets to update their versions to get the latest parquet version benefits. Review collected by and hosted on G2.com.

It's the best columnar storage forget we have used for our Hadoop system. Review collected by and hosted on G2.com.

Not efficient for all of our cases. For entire routes we prefer avro. Review collected by and hosted on G2.com.

Works with any table/data format we use. Review collected by and hosted on G2.com.

Can be difficult to load from s3 when files get too big Review collected by and hosted on G2.com.

Parquet is parallel ready, and columnar in nature Review collected by and hosted on G2.com.

libraries supporting parquet can be bit hard to find Review collected by and hosted on G2.com.

I am impressed at how well-designed the file format is. Best for big data/data analysis. Review collected by and hosted on G2.com.

It's a high learning curve. You have to think about the benefits versus the drawbacks Review collected by and hosted on G2.com.

The way the parquet-format project contain specifications format and properly formatted. Review collected by and hosted on G2.com.

The complex nature of the database for a simple project. Review collected by and hosted on G2.com.