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Why We Chose ClickHouse Over KDB+

Devon Edwards
October 2024
10 min read

KDB+ has long been the gold standard for financial time-series data. Its column-oriented architecture and the q programming language make it exceptionally fast for tick data analysis. So why are we increasingly recommending ClickHouse for new projects—and even migrating existing KDB+ deployments?

The Case for KDB+

Let's be clear: KDB+ is a remarkable piece of technology. Its strengths include:

  • Raw Query Speed: For certain query patterns, KDB+ remains unmatched
  • Memory Efficiency: Compressed in-memory storage with excellent cache utilization
  • Integrated Language: The q language allows complex analytics in concise expressions
  • Industry Pedigree: Battle-tested at the world's largest trading firms

If money were no object and you had access to experienced q developers, KDB+ would still be a strong choice.

The Reality Check

However, we've seen recurring challenges with KDB+ in practice:

Licensing Costs

KDB+ licensing is expensive—often $50,000+ per core per year for production use. For a firm running a 16-core production server with a hot standby and development environment, you're looking at $2M+ annually just for database licensing.

Talent Scarcity

The q programming language is notoriously difficult to learn. Experienced q developers are rare and command premium salaries. When your single q developer leaves, you have a serious business continuity problem.

Operational Complexity

KDB+ lacks many features that modern databases take for granted: no built-in replication, limited tooling for monitoring and administration, and challenging integration with modern DevOps practices.

Enter ClickHouse

ClickHouse, developed by Yandex and now maintained by ClickHouse Inc., is an open-source column-oriented database designed for real-time analytics. Here's why it's compelling for financial data:

Performance

In our benchmarks on tick data workloads, ClickHouse typically achieves 70-90% of KDB+ query performance—and sometimes exceeds it for certain query patterns. For most use cases, this is more than sufficient.

Query: VWAP calculation on 1 billion trades

KDB+: 0.8 seconds

ClickHouse: 1.1 seconds

Cost

ClickHouse is open-source with a permissive Apache 2.0 license. The managed ClickHouse Cloud service is available, but you can also run it yourself on commodity hardware. A typical migration saves 60-80% on database costs.

Accessibility

ClickHouse uses SQL. Your existing team already knows it. Hiring is straightforward. Onboarding new developers takes days, not months.

Modern Architecture

ClickHouse includes:

  • Built-in replication and sharding
  • Integration with Kafka, S3, and other data sources
  • Prometheus metrics and modern observability
  • Docker and Kubernetes support
  • Active open-source community

Migration Strategy

We've developed a proven migration methodology:

  1. 1.Schema Translation: Map KDB+ tables to ClickHouse with appropriate data types and partitioning
  1. 2.Query Migration: Convert q queries to SQL, optimizing for ClickHouse query patterns
  1. 3.Data Migration: Parallel export/import with validation
  1. 4.Performance Tuning: Optimize table engines, indices, and materialized views
  1. 5.Parallel Running: Run both systems in parallel during transition

When to Stick with KDB+

KDB+ remains the right choice when:

  • You need absolute lowest latency (sub-millisecond query times)
  • You have existing q expertise and codebase investment
  • Your use case requires complex vector operations that q handles elegantly
  • Cost is not a primary concern

Conclusion

For most financial firms, ClickHouse offers the best balance of performance, cost, and operational simplicity. If you're evaluating options for a new market data platform or considering a KDB+ migration, we'd be happy to share our experience and help you make the right decision.

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