Read, Create, Distribute, and Update Parquet files with ENZO using SQL commands or using DataZen's automatic data replication technology. Or you can use Enzo Explorer to view the content of Parquet files!
Choose your use case below to see which tool is best for your needs.
You can read Parquet files using both ENZO and DataZen. ENZO gives you the ability to query parquet files using the SQL language
from SQL Server Management Studio, while DataZen allows you to export to Parquet files and build/update
Data Lakes in Azure and AWS.
With ENZO, you can query Parquet files directly from SQL Server Management Studio.
ENZO is best for querying data sources ad-hoc and explore content directly within SQL Server Management Studio, in real-time.
With ENZO, Parquet files can be located on local hard drives or in the cloud, such as AWS S3 Buckets or Azure Blobs/ADLS.
ENZO provides limited support for updating Parquet files.
With DataZen you can read Parquet files to export data into other platforms, such as a relational database, other file
formats, or automatically detect changes made to Parquet files and forward these changes into a messaging hub of your choice.
In the screenshot below, you can see how DataZen allows you to select Parquet files using a wildcard name, for files
located on a local computer or in the clould (Azure ADLS Blobs and AWS Buckets), and only choose the select the data
that has changed since the last operation was run. With DataZen you can then easily copy the data found in Parquet
files into other database platforms, such as Azure SQL Database, MySQL, other file formats, HTTP REST endpoints or messaging
platforms.
DataZen supports Schema drifting across multiple Parquet files and allows you to apply filters using Data Pipelines.
Learn more about DataZen
Read the blog: Replicate Parquet files to SQL Server
With Enzo Explorer, you can view the content of Parquet files located on your local machine, shared drive, FTP sites, or
in the cloud (Azure Blobs/ADLS or AWS S3 buckets).
DataZen
Because DataZen is a replication technology with built-in change detection, including distribution of data based on bucketization rules,
and support for schema drifting over time,
creating or updating Parquet Files is best done with this platform. Parquet files can be located on a local drive, in Azure
Blobs/ADLS, or in AWS Buckets. Files can be updated directly, or new files can be created when changes are detected, supporting the
creation of a "Delta Lake".
In the example below, all the records replicated from a source system (such as a database table, or an HTTP REST endpoint) are sent
to a single Parquet file using the current timestamp as part of the file name.
Learn more about DataZen
Read the blog: Import Tweets as Parquet Files into Azure Synapse
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ENZO