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Ephedra

#22 of 25 in Data Integration

Ephedra: A SPARQL-based federation engine for teams querying heterogeneous data sources together. Ranked #22 of 25 in Data Integration by our editors (6.4/10); pricing: Pricing on request; best for teams joining graph and relational data with services.

6.4/10Editor score
Ephedra6.4 Visit Ephedra

At a glance

  • Editor score
    6.4 / 10
  • Pricing
    Pricing on request
  • Best for
    Teams joining graph and relational data with services
  • Deployment
    Cloud
  • Facts checked
    25 Sep 2026
Ephedra screenshot
  • Where it wins

    • Combines graph, relational, REST API and compute-service data
    • Supports full-text, spatial and other search in SPARQL queries
    • Uses union and join operations to combine partial query results
  • Where it doesn't

    • Specialized federation scope rather than a general integration platform
    • Contact-sales pricing makes costs harder to assess upfront
    • Presented for use with metaphactory, not as a standalone ELT product

Our verdict on Ephedra

Ephedra is a federation engine for teams that need to query graph databases, relational databases, compute services and REST APIs together. It uses SPARQL 1.1, with service interactions expressed through SERVICE clauses, and can connect RDF graph data with textual, temporal and geospatial data. The vendor describes use cases in engineering and manufacturing, pharma and life sciences, and open data. Its focus is on hybrid query federation rather than a broad connector-based integration workflow, so it fits teams with that specific query pattern better than organizations seeking a general-purpose integration platform.

The standout capability is how Ephedra combines data during query execution. It sends subclauses to relevant sources, extracts service-call parameters from SPARQL SERVICE clauses, gathers partial results, then combines those results through union and join operations. Full-text, spatial and other search can be included in SPARQL queries. The product also integrates dedicated services for graph analytics, statistical analysis and machine learning, while encapsulating external-service interactions in an RDF4J SAIL module. That makes it relevant when teams want graph queries to reach beyond RDF stores; its value depends on having the expertise and use case to work with SPARQL and federated sources.

Ephedra is presented alongside metaphactory rather than as a standalone connector-based ELT product, and the listed access channel is API. According to the vendor's pricing model, prospective buyers need to contact sales, which is less straightforward than a published self-serve plan. The product is cloud-deployed in its category profile, with email support and enterprise fit indicated. Specialized teams that need federated graph, relational and service queries should consider it; teams prioritizing broad integration workflows, transparent plan pricing or standalone ELT should look elsewhere.

Your product? Our editors can test Ephedra in depth and publish a review, labelled as paid · from $149/mo →

Ephedra pricing

Plans Pricing on request No free plan — trial or paid only. Prices checked 25 Sep 2026.
See plans on metaphacts.com

Ephedra fact sheet

Free planNot verified
Paid fromNot verified
DeploymentCloud
Prebuilt connectorsNot verified
Sync frequencyNot verified
Change data captureNot verified
Data transformationsAdvanced
Destination typesNot verified
DeploymentCloud
SupportEmail
Built forEnterprise (editorial estimate)
Integrations4 integrations: RDF graph databases, Relational databases, REST APIs, Compute services
PricingPricing on request
Websitemetaphacts.com
Facts checked25 Sep 2026

Ephedra integrations

Ephedra lists 4 integrations on its own site.

  • RDF graph databases
  • Relational databases
  • REST APIs
  • Compute services

Alternatives to Ephedra

See all Ephedra alternatives →

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Featured on iTechGuides

Featured on iTechGuides — Ephedra 6.4/10

Ephedra is listed in our Data Integration directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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