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Hopsworks

MLOps & Infrastructure · Predictive Analytics · Recommendation SystemsStockholm, SwedenFounded 2016

Hopsworks provides a unified SaaS platform for feature stores and MLOps, enabling organizations to build, deploy, and manage production-grade machine learning and real-time AI systems.

4.8
Average rating
13
Mapped reviews
100%
Profile coverage

Company & commercials

Primary category
MLOps & Infrastructure
Team size
25-50 employees
Typical budget
$100K+
Primary industry
Retail, Wholesale & Consumer Goods
Provider overview

A clear view of what Hopsworks does best.

Structured from supplied company information and mapped to RankGlobal's controlled AI and industry taxonomy.

Company profile
MLOps & Infrastructure provider for Retail, Wholesale & Consumer Goods

Hopsworks provides a unified SaaS platform for feature stores and MLOps, enabling organizations to build, deploy, and manage production-grade machine learning and real-time AI systems. RankGlobal maps its primary capability to Data Engineering for AI within MLOps & Infrastructure, with supporting relevance to GPU Infrastructure, Anomaly & Fraud Detection. Its strongest supplied industry signals align with General Retail, FinTech Platforms, HealthTech Platforms.

See how this profile was mapped →
Primary AI category
MLOps & Infrastructure
Strongest industry signal
Retail, Wholesale & Consumer Goods
Engagement profile·$100K+·25-50 employees·Product
Mapped capabilities · 6 categories
Technology

Platforms, methods and technical signals

Feature StoreAI LakehouseRonDBSparkFlink

Tools and platforms named in Hopsworks's supplied company profile.

Expertise

Named expertise on file

  • Feature Engineering

    Providing a high-performance "Feature Store" that streamlines the creation and management of data for ML models.

    Feature StoreData EngineeringML Pipelines
  • ML Lifecycle Management

    Orchestrating the end-to-end process from data ingestion to model serving and online monitoring.

    MLOpsModel GovernanceLifecycle
  • GPU Compute Orchestration

    Managing large-scale GPU resources for parallel model training and low-latency inference.

    GPU OrchestrationScale-Out TrainingInfrastructure
RankGlobal provider intelligence
Analyst brief

Mapped Evidence Report

A decision-support view of Hopsworks, built from mapped taxonomy signals, evidence confidence, commercial profile and reviews.

Primary feed set
MLOps & Infrastructure
Compared with
668 providers
Evidence signals used
3 signals
Publication status
Published
Structured evidence signal
100/100
Strong evidence
60th percentile of 668 peers · peer median 100
Profile coverage100
Taxonomy density100
Review signal100
Peer benchmark
How the profile compares

MLOps & Infrastructure among 668 published providers

Average rating4.81 · median 4.83
Mapped reviews13 · median 10
Profile completeness100% · median 100%
Taxonomy breadth30 · median 20
Signal radar
Multi-dimensional evidence
RatingReviewsCoverageBreadth
This profile (percentile) Peer median
Capability mix
Mapped category signal
MLOps & Infrastructure96%
Predictive Analytics88%
Recommendation Systems88%
LLM Agents & RAG80%

Imported mapping confidence for each category — not a share of work, revenue, or delivery volume.

Mapped industries
5 industries on the map
5
Aerospace, Defense & Space20%
Financial Services & Insurance20%
Healthcare & Life Sciences20%
Retail, Wholesale & Consumer Goods20%
Telecommunications & Connectivity20%

Share of mapped industry rows on the taxonomy map — not share of work or revenue.

Evidence mix
Mapping grades
Direct27% · 8
Supported50% · 15
Related23% · 7

Imported mapping grades across 30 taxonomy mappings — not a search ranking.

RankGlobal analyst interpretation

What the mapped signals say

Hopsworks presents as a strong evidence profile for MLOps & Infrastructure. It ranks in the 60th percentile of 668 published providers in MLOps & Infrastructure, and 13 reviews back the commercial profile.

Current positioning: P60 evidence quality · P93 industry breadth
Strongest signals
Evidence-backed strength in MLOps & Infrastructure is the profile's clearest signal in the mapped taxonomy.
Best user fit
Retail, Wholesale & Consumer Goods buyers evaluating MLOps & Infrastructure at a $100K+ engagement size.
Confirm before engagement
Confirm current delivery capacity directly — mapped signals reflect profile evidence, not live availability.
Client feedback signals
13
Reviews
4.8
Average rating
0
Publicly reshared
Published
Listing status
How this report is calculated →
Capabilities

Evidence-led AI expertise.

Capabilities are listed with their mapping grade (Direct, Supported, Related, or Adjacent).

Explore capabilities
Mapping grades
Direct
Supported
Related
Adjacent
Industry experience

Where this expertise is most relevant.

Industry mappings are organized by evidence strength so buyers can distinguish demonstrated alignment from broader search relevance.

5 mapped subindustries
Client feedback

What clients say.

Reviews and ratings published for this provider.

Our journey with Hopsworks has been an amazing transformation that's really enabled us to be innovative and reach a point that we wouldn't have been able to reach otherwise.

America First Credit Union

We ran extensive benchmarks comparing both setups and saw no noticeable performance degradation on Kubernetes. The reduced manual effort and built-in autoscaling were major wins for us. Performance remained on par while operational efficiency improved significantly.

Zalando

Hopsworks allowed us to cleanly separate features, models, and infrastructure, something that was extremely difficult to manage before, especially as a lean team operating real-time decision systems.

Clicklease
5
Bridging Data and ML via Industry-Leading AI Feature Stores

The feature store is the best in the market. It truly bridges the gap between data and ML.

Data Engineer
5
Simplifying Real-Time Inference via Low-Latency AI Access

Managing features for real-time inference is finally simple. The low-latency access is key.

ML Architect
5
Boosting Developer Productivity via Python-First AI Architectures

Python-first approach makes it very popular with our team. No need for complex Scala/Java.

Lead Data Sci.
5
Validating AI Security via Open-Source Cores and Enterprise Support

The open-source core gave us confidence, but the enterprise support is what we truly value.

CTO, Fintech
5
Ensuring Data Accountability via Airtight AI Feature Governance

Governance and lineage for features are airtight. We always know where our data came from.

DevOps Lead
5
Accelerating Pipeline Modernization via Professional AI Onboarding

Onboarding was professional. They helped us migrate our legacy data pipelines in record time.

Project Mgr

10 mapped reviews · 13 published quotes

Showing 9 of 13, ranked by display order then recency.

Rating distribution
5
10
4
0
3
0
2
0
1
0

Ratings aggregate 13 reviews at the average shown above.

Transparent profile intelligence

How RankGlobal maps this profile.

RankGlobal maps this profile against a controlled taxonomy. Mapping grades on capability and industry cards describe how the profile is classified. Source strength for ranking decisions follows the hierarchy published on Research— a mapping grade is not a claim of discoverability weight.

Tier 1 · Authoritative
Regulators, registries, certifications, signed client evidence.
Highest evidentiary weight
Tier 2 · Independent
Credible media, industry bodies, partner directories, third-party datasets.
Strong with attribution and recency
Tier 3 · Provider-controlled
Company site, case studies, press releases, structured submissions.
Accepted as a claim; verification raises weight
Tier 4 · Discovery-only
Directory listings, aggregations, and early discovery signals.
Used for discovery; weighted accordingly in ranking

Direct, Supported, Related and Adjacent appear on mapped cards as classification grades. They do not rank how discoverable a provider should be.

RankGlobal trust center →
Ready to evaluate this provider

Move from discovery to a focused conversation.

Your enquiry goes to the RankGlobal research team, not the provider's sales inbox. Sending it does not affect their ranking.

Before you reach out

What RankGlobal holds on file for Hopsworks, and the three things worth confirming directly once you're in touch.

Primary category
MLOps & Infrastructure
Primary industry
Retail, Wholesale & Consumer Goods
Typical budget
$100K+
Team size
25-50 employees
  1. 1
    Name the use case

    Say which MLOps & Infrastructure problem you are evaluating, so the research team can route your message accurately.

  2. 2
    Pressure-test the budget band

    The $100K+ band on file is a profile-level figure. Ask what a scope like yours actually lands at.

  3. 3
    Ask for a reference

    Request a client reference in Retail, Wholesale & Consumer Goods — the strongest industry signal on this profile.

Enquire about Hopsworks

Three fields. Anything longer belongs on the full contact page, linked below.

Hopsworks — AI Provider Profile | RankGlobal