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Syncsort Connect for Big Data [EOL] vs iWay Universal Adapter Framework comparison

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Buyer's Guide
Data Integration
April 2024
Executive Summary

We performed a comparison between iWay Universal Adapter Framework and Syncsort Connect for Big Data [EOL] based on real PeerSpot user reviews.

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Ranking
68th
out of 100 in Data Integration
Views
201
Comparisons
195
Reviews
0
Average Words per Review
0
Rating
N/A
Unranked
In Data Integration
Buyer's Guide
Data Integration
April 2024
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768,740 professionals have used our research since 2012.
Comparisons
Also Known As
Universal Adapter Framework, Information Builders Universal Adapter Framework
Syncsort DMX-h
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Information Builders
Precisely
Overview
iWay's Universal Adapter Framework contains more than 300 off-the-shelf adapters to provide easy access to any information system. With this breadth of data and application adapters, organizations can access data at every latency level from real-time, zero-latency transactions to staged data in the most summarized data mart.

Connect for Big Data is high-performance data integration software specifically designed for building modern data pipelines with highly scalable, distributed computer frameworks like Spark and MapReduce.

Sample Customers
RBC, City of Cincinnati, Pershing, Brotherhood Mutual, Friends University, Nationwide, City of Richardson, Cetera Financial Group
PagesJaunes
Buyer's Guide
Data Integration
April 2024
Download Free Report
Find out what your peers are saying about Microsoft, Informatica, Oracle and others in Data Integration. Updated: April 2024.
DOWNLOAD NOW
768,740 professionals have used our research since 2012.

iWay Universal Adapter Framework is ranked 68th in Data Integration while Syncsort Connect for Big Data [EOL] doesn't meet the minimum requirements to be ranked in Data Integration. iWay Universal Adapter Framework is rated 0.0, while Syncsort Connect for Big Data [EOL] is rated 0.0. On the other hand, iWay Universal Adapter Framework is most compared with CloverETL, whereas Syncsort Connect for Big Data [EOL] is most compared with .

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