Fivetran replicates applications, databases, events and files into a high-performance data warehouse, after a five minute setup. The vendor says their standardized cloud pipelines are fully managed and zero-maintenance. The vendor says Fivetran began with a realization: For modern companies using cloud-based software and storage, traditional ETL tools badly underperformed, and the complicated configurations they required often led to project failures. To streamline and accelerate…
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IBM StreamSets
Score 8.0 out of 10
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IBM® StreamSets enables users to create and manage smart streaming data pipelines through a graphical interface, facilitating data integration across hybrid and multicloud environments. IBM StreamSets can support millions of data pipelines for analytics, applications and hybrid integration.
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Fivetran
IBM StreamSets
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Fivetran
IBM StreamSets
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Premium Consulting/Integration Services
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Community Pulse
Fivetran
IBM StreamSets
Considered Both Products
Fivetran
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Anonymous
Chose Fivetran
Matillion requires a lot more initial setup effort and the resulting schemas are also much more "raw" data than the nicely cleaned schemas which Fivetran provides. Therefore it would also require more (manual) post-processing efforts compared to Fivetran. So the savings on time …
Fivetran is much easier to set up and maintain. Airbyte still had a degree of technical knowledge requirement that we didn't have the resources to commit. Fivetran allowed a non-technical employee to establish pipelines and immediately start using the data without having to …
We never seriously considered using anything else. Our data engineers had used Fivetran extensively in previous roles so when it came time to make a decision, there wasn't much of a process. They gladly signed the contract with Fivetran pretty quickly.
Fivetran came well with the connectors' availability and updates with the source changes. We had an idea on data requirements in our case which helped us to work out on cost implication and take a decision for Fivetran as a data provider for our organization. These were 2 …
Fivetran is more intuitive and easier to use than code-based ETL/ELT tools. The data modelling Fivetran performs makes the data more usable more quickly. Fivetran's dbt support and integration is unique.
Honestly, we haven't done much investigation in a while, it just works 360 days of the year. The other five days there may be a hiccup that will throw us a day off of data, but it gets caught up in the end.
At Unify Logistics, we chose IBM StreamSets over Fivetran for its flexibility in handling complex, real time data pipelines across hybrid environments. While Fivetran offers simplicity and fast setup, StreamSets provides deeper customization, better data drift handling, and …
First advantage is that this software is particularly new and it keeps updating according to the needs of the user. Other advantage is the it organises and produces conclusions on the basis of data without leaving any relevant information. Other softwares lack in data …
Before, we were using Informatica since most of our applications were running on on-prem servers. Later, when we started moving to the cloud, we tried Informatica Cloud, but it's more useful for batch-oriented than streaming. That's why one of our tech architects suggested IBM …
the IBM solution can be considered a good player in the specific perimeter of application because its main functionalities are working well, are easy to use, and complete. it allows also a good degree of freedom when it comes to personalization of pipelines and streams, and …
We chose IBM StreamSets because we used to own the product before selling it to IBM, so we have a tremendous amount of folks who are familiar with the product.
StreamSets is a one-stop solution to design Data engineering Pipelines and doesn't require deep Programming knowledge, It's so user-friendly that anyone in Team can contribute to the Idea of pipeline design. In Hadoop One has to be programming proficient to use its various …
[Fivetran is] very well suited when you are using popular and common data sources, such as the major ad platforms, and SaaS platforms such as Salesforce. If the majority of your data sources are custom internal applications or databases, may be less value as you aren't leveraging the delivered connectors.
When you are dealing with a data warehouse and want to find an easy way to integrate applications and expose data in real-time, then IBM StreamSets is the best tool to go for. I'm using it for the same purpose in my applications. This tool will be well-suited for someone with a proper technical background. Though IBM StreamSets UI is mostly drag and drop, advanced configurations require technical expertise or support to do the initial setup.
Very easy and intuitive to setup and maintain as there usually are not that many options. Very well documented (e.g. how to setup each connector, how the schema looks like, any specific features of this connector etc.). Also the operation is intuitive, e.g. you have status pages, log pages, configuration pages etc. for each connector.
because i think that overall the solution is having a positive impact on the business, it allows multiple benefits in simplification of the tasks and is capable of doing multiple process that are usually done by a combination of man and systems, reducing the time and effort required to have the data.
It runs pretty well and gets our data from point A to point cluster quickly enough. Honestly, it's not something I think about unless it breaks and that's pretty rare.
Fivetran came well with the connectors' availability and updates with the source changes. We had an idea on data requirements in our case which helped us to work out on cost implication and take a decision for Fivetran as a data provider for our organization. These were 2 places where Fivetran out-performed, other vendors.
At Unify Logistics, we chose IBM StreamSets over Fivetran for its flexibility in handling complex, real time data pipelines across hybrid environments. While Fivetran offers simplicity and fast setup, StreamSets provides deeper customization, better data drift handling, and stronger support for dynamic logistics workflows.