# What are the highest-rated wide-column databases for petabyte-scale analytical workloads in enterprise environments?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Hello G2’ers! I'm researching wide column databases for very large analytical workloads in enterprise settings. One honest note: reviews rarely quantify "petabyte-scale," so I'll go by which platforms enterprise reviewers actually run at very large scale for analytics, within the <a class="a a--md" elv="true" href="https://www.g2.com/categories/wide-column-database">Wide Column Database category</a>. These four carry the most enterprise-segment review evidence here.</p><ul>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/hbase/reviews"><strong>HBase</strong></a><strong>:</strong> The strongest enterprise-scale analytics story in the reviews, teams run it on Hadoop over billions of rows for big-data querying, ML pipelines, and reporting. The caveat is that heavy aggregation/OLAP is slower, and it needs Hadoop expertise.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/scylladb/reviews"><strong>ScyllaDB</strong></a><strong>:</strong> Enterprise reviewers run it for large-scale, high-throughput workloads with predictable latency on fewer nodes; the vendor targets petabyte-scale, and reviews back very large deployments, though it's more operational store than analytics engine.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/cassandra/reviews"><strong>Cassandra</strong></a><strong>:</strong> Long used at enterprises for massive datasets (call detail records, large event stores) with high availability. Reviewers note it's better for write-heavy access than complex analytical queries.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/microsoft-azure-cosmos-db/reviews"><strong>Microsoft Azure Cosmos DB</strong></a><strong>:</strong> Enterprise reviewers value global scale and SLA-backed performance, with Synapse Link cited for analytics on Azure. Cost at a sustained large scale is the recurring caveat.</li>
</ul><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Since I reframed this away from a literal petabyte claim, I'd genuinely like to hear from enterprise teams: at your largest scale, which of these held up for analytical querying specifically, and did you pair it with a separate analytics engine? What broke first at volume?</p>

##### Post Metadata
- Posted at: about 2 months ago
- Author title: Marketing
- Net upvotes: 1


## Comments
### Comment 1

&lt;p&gt;Something worth knowing: most wide column databases are great for operational access patterns and not so great for ad-hoc analytical queries at volume. HBase gets used in enterprise Hadoop setups for analytics but people almost always layer something like Hive or Phoenix on top to make it actually usable for reporting. If your workload is primarily analytical, you might be better served starting with a dedicated analytical engine and using the wide column store just for the hot path.&lt;/p&gt;

##### Comment Metadata
- Posted at: about 2 months ago
- Author title: SEO Content Specialist





## Related discussions
- [How well does Trello scale into a larger team?](https://www.g2.com/discussions/1-how-well-does-trello-scale-into-a-larger-team)
  - Posted at: over 13 years ago
  - Comments: 6
- [Can we please add a new section](https://www.g2.com/discussions/2-can-we-please-add-a-new-section)
  - Posted at: over 13 years ago
  - Comments: 0
- [Quantifiable benefits from implementing your CRM](https://www.g2.com/discussions/quantifiable-benefits-from-implementing-your-crm)
  - Posted at: over 13 years ago
  - Comments: 4