# What’s the leading ETL app for big data analysis?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">When data gets large enough, ETL stops being a background process and becomes a core part of how teams work with data. Looking at what the leading <a class="a a--md" elv="true" href="https://www.g2.com/categories/etl-tools">ETL app</a> for big data analysis is, the tools that stand out aren’t necessarily the easiest; they’re the ones that can handle scale without slowing everything down. That’s where Databricks, BigQuery, and IBM watsonx.data consistently come up.</p><ul>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/databricks/reviews">Databricks</a>: Built for distributed data processing, making it a go-to for large datasets and complex pipelines.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/google-cloud-bigquery/reviews">Google Cloud BigQuery</a>: Handles massive queries without infrastructure management, which simplifies big data workflows.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/ibm-watsonx-data/reviews">IBM watsonx.data</a>: Focuses on lakehouse architecture, helping unify structured and unstructured data.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/alteryx/reviews">Alteryx</a>: More visual and analyst-friendly, but still capable of handling complex transformations at scale.</li>
</ul><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">As data scales, what becomes harder to manage: performance, data consistency, or pipeline reliability?</p>

##### Post Metadata
- Posted at: 4 months ago
- Author title: Marketer
- Net upvotes: 1


## Comments
### Comment 1

&lt;p&gt;I&#39;m curious to know what the most unexpected challenge was once your data workloads reached scale?&lt;/p&gt;

##### Comment Metadata
- Posted at: 4 months ago
- Author title: Marketer





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