Talend Cloud Integration Competitors and Alternatives

Competitor
# Comparisons
Rating
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RM
Managing Director at a consultancy with 11-50 employees
Reseller
Top 20
Frees staff to focus on data workflow and on what can be done with data, and away from the details of the technology

What is our primary use case?

Equalum is used to take legacy data, siloed data and information in the enterprise, and integrate it into a consolidated database that is then used, for the most part, for data transaction, whether it's an actual transaction within the enterprise itself, or a BI dashboard. BI dashboards and analytics are a big area, but overall the main use case is for large data integration across disparate data sources. The way it's deployed is a combination of on-premises and cloud. It's mainly on-prem, but in Japan and Korea, the adoption of cloud is definitely nowhere near the same as in North America or… more »

Pros and Cons

  • "It's a really powerful platform in terms of the combination of technologies they've developed and integrated together, out-of-the-box. The combination of Kafka and Spark is, we believe, quite unique, combined with CDC capabilities. And then, of course, there are the performance aspects. As an overall package, it's a very powerful data integration, migration, and replication tool."
  • "It's got it all, from end-to-end. It's the glue. There are a lot of other products out there, good products, but there's always a little bit of something missing from the other products. Equalum did its research well and understood the requirements of large enterprise and governments in terms of one tool to rule them all, from a data migration integration perspective."
  • "They need to expand their capabilities in some of the targets, as well as source connectors, and native connectors for a number of large data sources and databases. That's a huge challenge for every company in this area, not just Equalum."

What other advice do I have?

It's a great tool to use in any data transformation opportunity, especially focusing on real-time. The word "batch" should never be used in an organization, going forward. I know it's useful and it has its use cases and there are situations where it's helpful. Batch is a form of history and it will probably always be there until that legacy finally disappears. But, overall, if anybody wants to look at migrating and transforming their overall data into a real-time enterprise, there's not a better tool in the market today, in terms of its performance, price, usability, and support. Those four…
CEO and Founder at HartB
Real User
Top 5
Improved our time to implement a new ETL process and has a good price and scalability, but only works with AWS

What is our primary use case?

It is a good tool for us. All the implementation in our company is done with AWS Glue. We use it to execute all the ETL processes. We have collected more or less five terabytes of information from the internet by now. We process all this data in our cloud platform and normalize the information. We first put it on a data lake that we have here on the AWS tool. After that, we use AWS Glue to transform all the information collected around the internet and put the normalized information into a data warehouse.

Pros and Cons

  • "The facility to integrate with S3 and the possibility to use Jupyter Notebook inside the pipeline are the most valuable features."
  • "The crucial problem with AWS Glue is that it only works with AWS. It is not an agnostic tool like Pentaho. In PowerCenter, we can install the forms from Google and other vendors, but in the case of AWS Glue, we can only use AWS."

What other advice do I have?

I would rate AWS Glue a seven out of ten.
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