Run affordable open source ClickHouse® anywhere with #AltinityCloud, Expert Support, BYOC, & real-time data lake integration to scale queries on cheap storage.
~10x cold read speedup vs AWS gp3. Database and workload on the same rack. $0 internal egress. ~70M rows/sec sustained from disk. That's #ClickHouse® on @nirvanalabsai, the new BYOC option for #AltinityCloud. Benchmarks & repos are public. 💪🏽
Learn more: hubs.la/Q04qTYZN0
Slow #ClickHouse® query? Start with the built-in tools. 💪🏽
▪ query_log: resources + runtime
▪ processors_profile_log: time per stage
▪ query_metric_log: live stats
▪ EXPLAIN + the chdig CLI
💡 Get the full breakdown: hubs.la/Q04xYzy60
Scaling #ClickHouse® storage without scaling compute? Meet CAS. 💥
Content-Addressed Storage (#CAS) adds shared object storage to existing MergeTree model, so storage can scale independently without replacing #MergeTree with a new engine.
CAS explained: hubs.la/Q04y7dTR0
0.65s vs. 1.42s on ~126M rows. Same #ClickHouse® table, same filter. The only change was the query’s ORDER BY. ⚡
If a query is sorting more than expected, check whether its ORDER BY matches the table’s: kb.altinity.com/engines/merg…
🎡 Hey Londoners, we'll be at the Data Engineering London #meetup tomorrow for an evening on Storage + #AI.
Expect deep dives on Hot SSDs to #lakehouses, data movement, metadata performance, and more.
📍 London Art Bar | 6 pm
🍻 Food + drinks on us
🔗 hubs.la/Q04xY3Lt0
Your analytical database is columnar & your dataframe library is too. But the path between them often isn't. That can mean extra copies & transposes to move query results. 😓
See how #ApacheArrow & #ADBC can eliminate that in this Unevenly Distributed ep: hubs.la/Q04xRPlG0
🇵🇱 Warsaw - thank you for making it an evening to remember.
Huge thanks to #OSACommunity for bringing everyone together, @dbcicero & other speakers for sharing the stage, & Josh Lee for hosting. Shoutout to everyone from the open source community who made the meetup so special.
Disk, memory, CPU, network. When #ClickHouse® has a problem, which one do you check first? 🤔
Our Sept. admin #training gets into ClickHouse internals so you can diagnose issues instead of guessing.
4 live sessions starting tomorrow (limited seats left): hubs.la/Q04x0mqb0
Above NKS: @AltinityDB.
The managed service for ClickHouse®: clusters, operator, console, monitoring, scaling, upgrades. Automatic backups, on-demand restore down to a single table.
The full breakdown, all episodes 👇
nirvanalabs.io/blog/altinity…#ClickHouse#BYOC
If older #ClickHouse® data is rarely queried, it may not need to stay on your fastest storage tier. 😎
#TTLs & tiered storage can keep recent data on fast block storage, move older data to S3, remove expired data automatically, & save storage cost by up to 30% (shown below). 👇🏻
A large export fails halfway through. So, restart from zero? 😬
While moving from #ClickHouse® ingestion to #ProjectAntalya, MindWise built o_rabbit so failed tasks retry independently & exports run in parallel.
⚡500GB export: 86 → 40 min on 4 workers: hubs.la/Q04wQWlJ0
A production incident is a bad time to learn how your #ClickHouse® cluster actually works. 🫠
Go deeper on storage, replication, resources, debugging, upgrades, monitoring, Keeper, & backups in 4 live Altinity #Administrator#Training sessions.
🚀 9/15: hubs.la/Q04x1Ny10
More partitions ≠ faster #ClickHouse®. 👎🏻
Too-granular partitioning means more parts, more files, more background work, & potentially more remote-storage requests.
Use PARTITION BY for the job it’s meant to do, not as a generic faster-SELECT switch.
👉🏻 hubs.la/Q04vVpxz0
“Have you guys called Altinity yet?” - Avi Press, CEO of @scarf_oss
As the data grew 200–300x, Scarf needed to bring #ClickHouse® costs under control. With Altinity’s help, they moved to #BYOC, optimized the schema & queries, & brought #TCO down by 60%.
hubs.la/Q04wQWnq0
Optimize the #SQL or add more hardware? 🤷🏻♀️
For ClickHouse®, optimize first. If traffic forces you to scale, scale. Then come back to the workload and right-size again.
Scale for demand, not inefficiency.
💰 See what actually lowers #ClickHouse costs: hubs.la/Q04vT_Wl0
Your slowest #ClickHouse® query may be the wrong one to optimize first.
A fast query running thousands of times can drive more total load than one obvious slow query. system.query_log + normalized_query_hash can help surface the patterns actually worth your optimization time. 👇🏻
#BYOC sounds great until the obvious question comes up: are you getting more control, or just taking on more ops? 🤔
Tomorrow in SF, we dig into that with #ClickHouse® as the example: where ops end, customer control begins, and when BYOC works well.
🎟️ hubs.la/Q04tQwt70
"The #AI agent dropped a table in production" is a sentence nobody wants to say in a postmortem. 😬
The fix? Put the boundary where the agent can't talk its way around, using #ClickHouse® RBAC, OAuth, and MCP server.
⚙️ See how to fit all three together: hubs.la/Q04vRNtw0