name: Manticore Search FinOps
description: Financial operations guidance for Manticore Search deployments. As an open-source self-hosted solution, costs are driven by infrastructure rather than API call pricing.
url: https://manticoresearch.com/services/
license: GPLv3
open_source: true

cost_model:
  type: infrastructure
  description: Manticore Search itself is free under GPLv3. Total cost of ownership is determined by hosting infrastructure, storage, compute, and optional commercial support contracts.

infrastructure_costs:
  - category: Compute
    description: Manticore Search can run on minimal resources. Baseline is 1 core and 1GB RAM, though production workloads typically require more depending on dataset size and query volume.
    minimum_viable: "1 vCPU, 1GB RAM"
    recommended_production: "4+ vCPU, 8GB+ RAM"

  - category: Storage
    description: Columnar and row-wise storage options. Storage costs scale with index size and number of documents.

  - category: Network
    description: Data transfer costs for replication across nodes or regions when using multi-master replication.

managed_service_costs:
  - provider: Elestio
    url: https://elest.io/open-source/manticoresearch
    starting_price: 11
    currency: USD
    period: month
    includes:
      - Managed infrastructure
      - Automated backups
      - SSL certificates
      - Automated updates
      - 24/7 monitoring
      - Multi-cloud and multi-region support

support_costs:
  - tier: Community
    cost: 0
    currency: USD
    period: month
    description: Free community support via forum, Slack, Telegram, and GitHub.

  - tier: Standard
    cost: contact
    currency: USD
    period: month
    description: Commercial SLA-backed support with dedicated Technical Account Manager. Contact sales for pricing.

  - tier: Enterprise
    cost: contact
    currency: USD
    period: month
    description: Full-service enterprise support with custom feature development and private branch maintenance. Contact sales for pricing.

cost_optimization_tips:
  - Use columnar storage for analytical workloads to reduce memory usage.
  - Leverage secondary indexes (PGM-index) to speed up queries and reduce CPU costs.
  - Use real-time indexes for frequently updated data and plain indexes for static datasets.
  - Enable replication only when high availability is required to control infrastructure costs.
  - Start with minimal resources and scale based on actual query volume and latency requirements.

contact:
  email: support@manticoresearch.com
  enterprise: info@manticoresearch.com
  enterprise_url: https://manticoresearch.com/contact-enterprise/