Ascend Data Ingestion Platform

Data Ingest

Seamlessly connect your data pipelines to any data, in any system, without worrying about yet another system or tool.

Fast, Repeatable Data Ingestion and Replication

Ingest Data from Any Source in Any Format​

Choose from an expanding library of flex-code data connectors 

Create your own connectors with little to no code needed

Cross-Cloud Data Replication​

Quickly replicate from cloud-to-cloud with a simple data pipeline 

Optimize cross-cloud data transfers

Flex-Code Connector/
Connections Reuse​

Build a connector once, and use it forever

Flex-Code Data Connectors can be used by you or anyone on your team

Automatic Data Profiling​

Automatically profile every piece of data

See how values change over time

Easily keep an eye on data anomalies and more.

Incremental Data Propagation

Save significant infrastructure costs by processing end-to-end data faster

Automatically handle later arriving data

Only process changed data—and data related to it—without re-processing unchanged data

Automatic Data Reformatting​

Quickly get all your data—big and small—ready for processing

Aggregate small files and partition large files with ease

Quickly convert GZIP’ed CSVs to Snappy compressed Parquet files

Quickly parse and reformat text JSON, CSV, Avro, Parquet and more.

Full support for all standard industry compression such as GZIP, BZIP, etc.

Extend Ascend by implementing your own custom Python parser

Automatic Data Detection​

Detect and ingest new, updated, and deleted data automatically, and efficiently

Keeps tabs on data connectors to know not only where your data is located but also how often it changes

Know what data has already been ingested

Want to learn more about the data ingestion platform and how it can help you quickly and easily bring advanced automation to your data and analytics engineering efforts with the Ascend Data Automation Cloud?

From Our Customers

Resources

The New Data Scale Challenge
From struggling with data volume and infrastructures to scaling data team capacity—what is the answer to increasing bandwidth?
Whitepaper
DataAware Podcast
With a variety of guests from all facets of data engineering and associated teams, episodes look in-depth at the role of data engineering and data teams, trends, best (and worst) practices, real world use cases, and more.
PODCAST
A Deep Dive Into Data Orchestration at Harry's
Learn how the Harry's data science team expedited ingesting, transforming, and delivering retail data feeds into a new, robust shared data model.
Video