Skip to content

Remove hard upper memory limits from FAQ and ClickHouse docs #570

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We鈥檒l occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
worldsoup merged 1 commit into from
Sep 30, 2026
Merged

Remove hard upper memory limits from FAQ and ClickHouse docs #570

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion docs/about/faq.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@ For teams that want out-of-the-box scaling, security, and expert support, we lau

## How does Dragonfly's vertical scaling compare to a Redis cluster?

Dragonfly utilizes the underlying hardware in an optimal way. This means that it can run on small 8GB instances and scale vertically to large 768GB machines with 64 cores. This versatility allows for far less complexity as well as lower infrastructure costs when compared to running cluster workloads. In addition, Redis cluster-mode imposes some limitations on multi-key and transactional operations while Dragonfly provides the same semantics as a single node Redis.
Dragonfly utilizes the underlying hardware in an optimal way. This means that it can run on small 8GB instances and scale vertically to the largest multi-terabyte machines. This versatility allows for far less complexity as well as lower infrastructure costs when compared to running cluster workloads. In addition, Redis cluster-mode imposes some limitations on multi-key and transactional operations while Dragonfly provides the same semantics as a single node Redis.

## When will you support X command?

Expand Down
3 changes: 1 addition & 2 deletions docs/integrations/clickhouse.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -94,11 +94,10 @@ However, if range queries are required, ClickHouse can still utilize the `SCAN`
- Point query example -- `WHERE key = xx` or `WHERE key IN (xx, yy)`
- Range query example -- `WHERE key > xx`

Dragonfly is able to support up to 1TB on a single instance.
Dragonfly supports multi-terabyte datasets on a single instance.
Redis, on the other hand, is typically constrained to handling tens of GB on an individual instance.
Further, the use of Redis Cluster, which might seem like a solution, is off the table as it doesn't support the `SCAN` command in its cluster mode.
Hence, for applications requiring expansive datasets and range queries, Dragonfly stands as the most effective and reliable choice for the key-value table engine when paired with ClickHouse.
We do understand that 1TB is probably not "big data" in modern terms, but supporting 1TB on a single instance is still an advantage and should be sufficient for many ad-hoc analytics use cases.

## Useful Resources

Expand Down
Loading