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Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Ascend provides data teams with a streamlined and automated platform that allows them to ingest, transform, and orchestrate their entire data engineering and analytics workloads at an unprecedented speed, achieving results ten times faster than before. This tool empowers teams that are often hindered by bottlenecks to effectively build, manage, and enhance the ever-growing volume of data workloads they face. With the support of DataAware intelligence, Ascend operates continuously in the background to ensure data integrity and optimize data workloads, significantly cutting down maintenance time by as much as 90%. Users can effortlessly create, refine, and execute data transformations through Ascend’s versatile flex-code interface, which supports the use of multiple programming languages such as SQL, Python, Java, and Scala interchangeably. Additionally, users can quickly access critical metrics including data lineage, data profiles, job and user logs, and system health indicators all in one view. Ascend also offers native connections to a continually expanding array of common data sources through its Flex-Code data connectors, ensuring seamless integration. This comprehensive approach not only enhances efficiency but also fosters stronger collaboration among data teams.

Description

DataNimbus, an AI-powered platform, streamlines payments and accelerates AI implementation through innovative solutions. DataNimbus improves scalability and governance by seamlessly integrating Databricks components such as Spark, Unity Catalog and ML Ops. Its offerings include a designer, a marketplace of reusable connectors and blocks for machine learning, and agile APIs. All are designed to simplify workflows while driving data-driven innovation.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

No images available

Integrations

Databricks Yes 
Amazon Redshift Yes 
Amazon S3 Yes 
Apache Kafka Yes 
Apache Spark No 
Azure Data Factory Yes 
Azure Event Hubs Yes 
Delta Lake Yes 
Google Cloud BigQuery Yes 
Google Cloud Managed Service for Apache Spark Yes 
Microsoft Azure Yes 
Microsoft Power BI Yes 
MongoDB Yes 
PostgreSQL Yes 
QlikMaps Yes 
Snowflake Yes 
Tableau Yes 
Unity Catalog No 
Vertica Yes 
Vidora Cortex Yes 

Integrations

Databricks Yes 
Amazon Redshift No 
Amazon S3 No 
Apache Kafka No 
Apache Spark Yes 
Azure Data Factory No 
Azure Event Hubs No 
Delta Lake No 
Google Cloud BigQuery No 
Google Cloud Managed Service for Apache Spark No 
Microsoft Azure No 
Microsoft Power BI No 
MongoDB No 
PostgreSQL No 
QlikMaps No 
Snowflake No 
Tableau No 
Unity Catalog Yes 
Vertica No 
Vidora Cortex No 

Pricing Details

$0.98 per DFC
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs No 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Ascend

Country

United States

Website

www.ascend.io

Vendor Details

Company Name

DataNimbus

Founded

2018

Country

United States

Website

datanimbus.com

Product Features

Data Management

Customer Data No 
Data Analysis No 
Data Capture No 
Data Integration No 
Data Migration No 
Data Quality Control No 
Data Security No 
Information Governance No 
Master Data Management No 
Match & Merge No 

ETL

Data Analysis No 
Data Filtering No 
Data Quality Control No 
Job Scheduling No 
Match & Merge No 
Metadata Management No 
Non-Relational Transformations No 
Version Control No 

Product Features

Data Management

Customer Data No 
Data Analysis No 
Data Capture No 
Data Integration No 
Data Migration No 
Data Quality Control No 
Data Security No 
Information Governance No 
Master Data Management No 
Match & Merge No 

ETL

Data Analysis No 
Data Filtering No 
Data Quality Control No 
Job Scheduling No 
Match & Merge No 
Metadata Management No 
Non-Relational Transformations No 
Version Control No 

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