# What Big Data Analytics platform is most trusted by data engineers and senior engineers, based on user reviews?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Data engineers trust a <a class="a a--md" elv="true" href="https://www.g2.com/categories/big-data-analytics">Big Data Analytics platform</a> based on something pretty unglamorous: whether a pipeline that ran fine at a million rows still runs fine at a billion, without quietly falling over.</p><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Databricks, Snowflake, and Google Cloud BigQuery dominate this space:</p><ol>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/databricks/reviews"><strong>Databricks</strong></a><strong>:</strong> 4.6 stars across 1,363 reviews, built on Apache Spark by its original creators, used by more than 20,000 organizations, including 70% of the Fortune 500.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/snowflake/reviews"><strong>Snowflake</strong></a><strong>:</strong> 4.6 stars across 762 reviews, matches Databricks' rating; its AI Data Cloud powers data sharing and application building for thousands of companies.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/google-cloud-bigquery/reviews"><strong>Google Cloud BigQuery</strong></a><strong>:</strong> 4.5 stars across 1,223 reviews, a petabyte-scale data warehouse built for near real-time analytics at serious scale.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/alteryx/reviews"><strong>Alteryx</strong></a><strong>:</strong> 4.6 stars across 894 reviews, trusted by over half of the Global 2000, focused on cleansing and blending disconnected data into an AI-ready state.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/qubole/reviews"><strong>Qubole</strong></a><strong>:</strong> 4.0 stars across 259 reviews, the lowest rating here, an open data lake platform trusted by brands like Expedia and Disney for streaming and ad-hoc analytics.</li>
</ol><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">For engineers who've actually scaled a pipeline from a proof-of-concept to real production volume on one of these, what broke first, the query performance, the cost, or something else entirely?</p>

##### Post Metadata
- Posted at: 7 days ago
- Author title: Writer
- Net upvotes: 1


## Comments
### Comment 1

&lt;p&gt;I’d expect cost and workload management to become the real stress test after query performance. A platform can scale technically, but if teams have to constantly tune clusters, warehouses, or jobs to keep spend predictable, that operational overhead adds up fast.&lt;/p&gt;

##### Comment Metadata
- Posted at: 7 days ago
- Author title: Marketer





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