Elasticsearch vs Meilisearch Cloud Search

Elasticsearch vs Meilisearch Cloud Specs
  • Free Tier Allowance
  • Rate Limit Cap
  • Session Lifetime
  • Overage Fee per 1k MAU
Comparison chart between Elasticsearch and Meilisearch Cloud raw data
MetricElasticsearchMeilisearch Cloud
Free Tier AllowanceSelf-Hosted Only100,000 Records
Rate Limit CapCluster Bound1,000 Concurrent Requests
Session Lifetime24 Hours24 Hours
Overage Fee per 1k MAU$015 USD/node
Deploy Elasticsearch
👉 Open Source Core • Unbound Enterprise Cluster Search
Deploy Meilisearch Cloud
👉 100,000 Free Records • Typos-Tolerant Search API
Elasticsearch
Free Tier Allowance:
Self-Hosted Only
Rate Limit Cap:
Cluster Bound
MFA Support:
Enforced via Elastic Cloud console MFA and SAML-enforced organization login
Enterprise SSO SAML:
Supported on Enterprise plans with SAML, OIDC, and RBAC
Custom Domain Support:
Custom domains and private endpoints on Elastic Cloud Enterprise
Supported SDKs:
JavaScript, Python, Java, Go, Ruby, PHP, .NET, REST, Elasticsearch DSL
Social Providers:
Google and corporate SSO for Elastic Cloud account management
Compliance Standards:
SOC 2 Type II, ISO 27001, HIPAA, PCI-DSS, GDPR on Enterprise tiers
Webhook Fallback Policy:
Watcher alerts and ingest pipelines with dead-letter index replay patterns
Meilisearch Cloud
MFA Support:
Enforced via Meilisearch Cloud account two-factor authentication
Enterprise SSO SAML:
Available on Enterprise plans with SAML and organization RBAC
Custom Domain Support:
Custom API endpoints and dedicated instances on Enterprise tiers
Supported SDKs:
JavaScript, Python, PHP, Ruby, Go, Rust, Java, .NET, Dart
Social Providers:
GitHub OAuth for cloud project provisioning
Compliance Standards:
SOC 2 Type II, GDPR; HIPAA on Enterprise agreements
Webhook Fallback Policy:
Task webhooks with status polling and configurable retry on failed batches
Elasticsearch
Use index lifecycle management to roll hot indices to warm tiers and control storage costs on long-retention log data.
Meilisearch Cloud
Enable embedders in the same index to blend keyword relevance with semantic vectors without a separate vector database.