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Head-to-head · Time-Series Databases

kdb+ vs Prometheus

  • Updated Oct 2026
  • Both researched from official sources
  • 4 checks side by side
Higher score kdb+ #4 in Time-Series Databases 8.9/10 Pricing on request ✓ 3 of 3 features Visit kdb+
Prometheus #5 in Time-Series Databases 8.8/10 Free plan Free plan✓ 1 of 3 features Visit Prometheus

kdb+ leads on 2 checks, Prometheus on 0, and 2 are even. Who comes out ahead on the 4 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scorekdb+ · 8.9/10
  • Free planonly Prometheus
  • Most featureskdb+ · 3 of 3

kdb+ scores higher on our rubric for time-series databases: 8.9 against 8.8 out of 10; our editors rank them #4 and #5.

On deployment, kdb+ gives you Both where Prometheus offers Self_hosted. kdb+ offers sql support; Prometheus doesn't. kdb+ offers horizontal scaling; Prometheus doesn't.

kdb+ is the better fit for high-performance financial time-series processing. Prometheus is the better fit for prometheus-native monitoring metrics.

  • kdb+ fits best

    High-performance financial time-series processing

  • Prometheus fits best

    Prometheus-native monitoring metrics

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Side by side

Feature kdb+ 8.9/10 Visit ↗ Prometheus 8.8/10 Visit ↗
At a glance
Editor score 8.9 8.8
Ranking #4 in Time-Series Databases #5 in Time-Series Databases
Best for High-performance financial time-series processing Prometheus-native monitoring metrics
Pricing model Paid Free
Starting price Pricing on request Free plan
Free plan Not checked yet ✓ (best)
Free trial — —
Deployment Cloud, Self-hosted Self-hosted
Platforms Windows, macOS, Linux Web, Windows, macOS, Linux
Support Community, Docs Community, Docs
Integrations 17 integrations 8 integrations
Built for Mid-market, Enterprise Small business, Mid-market, Enterprise
Features kdb+ 3/3 · Prometheus 1/3
SQL support ✓ (best) —
Retention policies ✓ ✓
Horizontal scaling ✓ (best) —
Specs
Deployment Both Self_hosted
Query languages q, q-SQL PromQL
Ingestion methods tickerplant, feed handlers, batch mode, TCP/IP, Apache Kafka, Python, Java, C HTTP pull scraping; Pushgateway; Remote Write; OpenMetrics backfilling
Our review
Pros
  • Columnar storage with in-memory real-time processing
  • Tickerplant, feedhandler, and partitioned historical database architecture
  • Integrations across ODBC, Kafka, Java, Python, C, and R
  • PromQL supports selecting and aggregating labeled time-series data.
  • HTTP scraping, service discovery, and exporters support metric collection.
  • Recording rules, Alertmanager, federation, and remote storage extend monitoring.
Cons
  • Self-hosted deployment requires infrastructure ownership
  • Closed-source licensing limits source-level customization
  • Pricing requires contacting sales
  • No SQL support for querying time-series data.
  • Local storage is single-node rather than horizontally scaled.
  • Broader architectures require federation or remote-storage integrations.
Our verdict

kdb+ is a time-series database and analytics engine for organizations processing real-time and historical data. Its design combines columnar storage, in-memory execution, persistent databases, temporal data types, and the q programming and…

Read the review →

Prometheus is an open-source monitoring and alerting toolkit for infrastructure, applications, and services, particularly in dynamic and microservice-oriented environments. It collects numeric metrics through HTTP-based scraping and stores…

Read the review →
  1. kdb+Time-Series Databases 8.9Pricing on request
  2. PrometheusTime-Series Databases 8.8Free plan

Strengths and trade-offs

  • kdb+ — where it wins

    • Columnar storage with in-memory real-time processing
    • Tickerplant, feedhandler, and partitioned historical database architecture
    • Integrations across ODBC, Kafka, Java, Python, C, and R

    Where it doesn't

    • Self-hosted deployment requires infrastructure ownership
    • Closed-source licensing limits source-level customization
    • Pricing requires contacting sales

  • Prometheus — where it wins

    • PromQL supports selecting and aggregating labeled time-series data.
    • HTTP scraping, service discovery, and exporters support metric collection.
    • Recording rules, Alertmanager, federation, and remote storage extend monitoring.

    Where it doesn't

    • No SQL support for querying time-series data.
    • Local storage is single-node rather than horizontally scaled.
    • Broader architectures require federation or remote-storage integrations.
  • kdb+8.9/10 · Pricing on request

    A specialized, self-hosted engine for real-time and historical financial analytics.

    Visit kdb+Full verdict →
  • Prometheus8.8/10 · Free plan

    A Prometheus-native metrics platform with PromQL, alerting, retention, and federation.

    Visit PrometheusFull verdict →

More comparisons

All Time-Series databases comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update