Migrate to ClickHouse With Zero Downtime & Ops Overhead

Get guidance from the team that’s helped enterprises migrate to open source ClickHouse and handle schema rewrites, system quirks, and post-migration bottlenecks at petabyte scale.

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ClickHouse is a great database if you’re looking for: sub-second queries on billions of rows, lower infra costs compared to legacy OLAP, real-time analytics, huge open source community, no licensing fees; full transparency, flexible SQL analytics.

But many teams hit blockers during migration:

“JOINs aren’t working the way we expect”

“Our schema doesn’t map cleanly”

“We can’t afford downtime or surprises”

“We’re struggling with data deduplication”

“Text search capabilities are lacking”

“Our queries get killed or time out”

When it comes to migration rollout, understanding what ClickHouse handles well, what needs tuning before you make the switch, and how it fits in your tech stack is a good strategy.

Common ClickHouse Migration Use Cases We Support

  • Replacing Elasticsearch with high-speed search + analytics
  • Moving off InfluxDB for better compression + performance
  • Offloading heavy analytics from your OLTP database (i.e., Postgres) without rewriting your entire schema
  • Migrating from cloud warehouses (like Snowflake or BigQuery) to cut costs
  • Migration from managed vendor to self-hosted or vice versa (if you don’t know which option is right for you, we can also help with that)
Source
ClickHouse

Frequently Asked Questions about ClickHouse and ClickHouse migrations

ClickHouse can process billions of rows per second, enabling sub-second response times for complex analytical queries, even on modest hardware. Visit our What is ClickHouse page for more information on ClickHouse.

At Altinity, we help you break the migration process down into clear, manageable steps:

1. Assess your current workload: We start by understanding your existing system, whether it’s Elasticsearch, InfluxDB, Postgres, Snowflake, or another platform, includes query patterns, data volume and schema, and latency and performance goals.

2. Map to ClickHouse: We identify how your data model, indexes, and access patterns translate to ClickHouse’s architecture, optimizing for compression, speed, and scalability.

3. Set up a ClickHouse POC: Before committing, we help you stand up a working ClickHouse cluster (cloud or self-managed) with a sample of your real data. This lets you validate performance and compatibility early.

4. Migrate incrementally: Firstly, we design a staged migration plan: query rewrites (only where needed), minimal disruption to production, data ingestion pipelines, and schema translation.

5. Optimize ClickHouse: Once live, we help with performance tuning, monitoring & alerting, cost optimization, and scaling strategies


Want to explore your path? Talk to us. We’ve done this hundreds of times.

Yes. Altinity engineers have many decades of experience running ClickHouse. We have contributed thousands of PRs and have our own builds for ClickHouse. Moreover, our popular Altinity Kubernetes Operator for ClickHouse has been downloaded over 100M times.

Whether you plan to use ClickHouse for BI, log analytics, AI/ML, obeservalibity, SIEM, or time series, our team of ClickHouse specialists can help! We have solved complex migration challenges, including schema transitions, OLTP to OLAP compatibility, migration rollback, integration tooling, external engine compatibility, data validation, and post-migration performance optimization. We follow a rigorous process to ensure you get the most out of ClickHouse and that it’s the best fit for your use case.

Get Expert Advice for free.

There’s no one-size-fits-all for ClickHouse migration. Let’s help you figure out your best path, even if it means not choosing ClickHouse right now.