
About Hopsworks
Hopsworks is a cloud-based and on-premise solution, which helps businesses in automotive, betting, finance and healthcare industries design and operate machine learning (ML) applications. Key features include data preparation, model validation, version control, model serving, and monitoring.
It enables developers to collect data from multiple structured and unstructured sources and perform validation in order to create training data for models. The solution allows professionals to annotate models with metadata, letting developers perform root cause analysis and discover bugs across models. Engineers can prepare ML pipelines in Python language and design production code in the Jupyter Notebook for further execution. Hopsworks offers GDPR-compliant secure storage to manage sensitive datasets, grant users role-based access, and prevent data export from the project. Moreover, with the solution’s Airflow Operator feature, professionals can track errors and receive notifications about production problems in real-time.
Hopsworks comes with a feature store module, which enables data scientists to discover, analyze, and reuse features across applications, add new features, and create curated data for machine learning algorithms. It also ensures consistency in the feature engineering process, executes time-travel queries, and generates high-quality data using validation tools. Plus, the solution assists users with both stream and data-parallel processing via the Apache Spark, Apache Flink, and Apache Beam applications.
Pricing starting from:
US$1,00/month
- Free Trial
- Free Version
- Subscription
Key benefits of Hopsworks
- End-to-End ML Pipelines - the Feature Store to training to serving
- Manages ML Assets: Features, Experiments, Model Repository/Monitoring
- Project-based multi-tenancy - collaborate with sensitive data in a shared cluster
- Enterprise integrations with Active Directory, LDAP, OAuth2, Kubernetes
- Full governance and provenance for ML assets, with GDPR compliance
- Open-source ML with Spark, TensorFlow, PyTorch, Scikit-Learn
- Solves the hardest scaling problems: training, hparam tuning, feature engineering
Devices
Business size
Markets
Supported Languages
Pricing starting from:
US$1,00/month
- Free Trial
- Free Version
- Subscription
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Features
Total features of Hopsworks: 51
- API
- Access Controls/Permissions
- Applications Management
- Batch Processing
- Behavior Tracking
- Bug Tracking
- Collaboration Tools
- Customer Database
- Data Analysis Tools
- Data Cleansing
- Data Discovery
- Data Integration
- Data Migration
- Data Quality Control
- Data Security
- Data Transformation
- Data Verification
- Data Visualization
- Data Warehousing
- Deep Learning
- Event Logs
- For Healthcare
- For eCommerce
- High Volume Processing
- Historical Reporting
- Information Governance
- Issue Tracking
- ML Algorithm Library
- Machine Learning
- Master Data Management
- Metadata Management
- Model Training
- Monitoring
- Multiple Data Sources
- Natural Language Processing
- Pipeline Management
- Predictive Analytics
- Predictive Modeling
- Process/Workflow Automation
- Project Management
- Projections
- Real Time Notifications
- Reporting/Analytics
- Role-Based Permissions
- Search/Filter
- Secure Data Storage
- Statistical Modeling
- Templates
- Third Party Integrations
- Version Control
- Visualization
Alternatives
Centralpoint

eLegere

Tableau

Data Fabric

Reviews
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- Industry: Financial Services
- Company size: 10 000+ Employees
- Used Other for 1+ year
-
Review Source
Overall rating
- Value for Money
- Ease of Use
- Customer Support
- Likelihood to recommend 9.0 /10
Skilled challenger to our Teradata suit
Reviewed on 2020/02/14
Pros
Hopsworks keeps us as a big organisation to be on our toes, in terms of what is possible and how fast it can be implemented. Nice to have options of on-premise and cloud, and extremely fast to add new libraries and other custom made wished from the data scientists.
Cons
Sometimes as it's rather flexible and fast to implement it can be hard to place it and understand it's belonging in our overall data architecture.
- Industry: Hospital & Health Care
- Company size: 51-200 Employees
- Used Daily for 2+ years
-
Review Source
Overall rating
- Ease of Use
- Customer Support
- Likelihood to recommend 10.0 /10
Hopsworks
Reviewed on 2020/04/12
We recently analysed terabytes of cancer sequencing data and estimated what proportions of the...
We recently analysed terabytes of cancer sequencing data and estimated what proportions of the cancers might be preventable in the future by vaccination. The paper is about to publish any day now and this study would have been impossible without Hopsworks.
Pros
As a data scientist, I am mostly focusing on developing big data processing pipelines as well as feature engineering for which Hopsworks is probably one of the best platforms. It makes it very easy to run Spark or PySpark applications to process vast amount of data with available resources. Installing python libraries for Jupiter notebook is also quite straightforward which solves many painful problems for a data scientist.
Cons
One thing I would try to improve is to get better visibility of the logs after a job is completed.
- Industry: Information Technology & Services
- Company size: 51-200 Employees
- Used Other for 1+ year
-
Review Source
Overall rating
- Ease of Use
- Likelihood to recommend 8.0 /10
Hopsworks trial review
Reviewed on 2020/02/11
Pros
- project oriented dat plateform
- huge set of data analytics features (feature store, automl, lakehouse, kafka, spark, flink, ....)
- devsecops oriented product (security, stretched cluster, model serving, scm, ...)
- on-premise, cloud , multi-cloud (potential) and hybrid-cloud (potential) platform
- easiness of use
- european company
- open source based product
- gdpr compliancy
- deep learning compliancy (gpu, tpu(?), pytorch, tensorflow)
- openess (databricks, sagemake, ..., connectors)
- ...
Cons
- Hudi instead of deltalake
- lack of connection between deltalake (as provided with Hudi) and the feature store
- unability to use the ELK or influxdb included tools
- lack of connectors with AzureML, driveless ai, powerbi, azure datablob storage, snowflake, ...
- lack of managed platform on azure or gcp as the one provided for aws
- how to handle staging environment especially for the data sharing?
- ability to deploy on a kubernetes environment outside hopsworks
- R connection along with Python
- difficulties to knwo the arguments for choosing hopsworks instead of dtabacricks, azureml, sagemaker, ....
- lack of prepackaged, ready-to-use managed platform on an appliance for including intot a private datacenter
- I don't know the pricing policy, and I'm not capable of comaring it with the competitor ones
- no graphical etl-like tools enabling to create quickly a data engineering process and deploy it (à la dremio or dataiku)
Hopsworks FAQs
Below are some frequently asked questions for Hopsworks.Q. What type of pricing plans does Hopsworks offer?
Hopsworks offers the following pricing plans:
- Starting from: US$1,00/month
- Pricing model: Free, Subscription
- Free Trial: Available
Contact Logical Clocks for more details
Q. What are the main features of Hopsworks?
We do not have any information about Hopsworks features
Q. Who are the typical users of Hopsworks?
Hopsworks has the following typical customers:
2-10, 11-50, 51-200, 201-500, 501-1 000, 1 001+
Q. What languages does Hopsworks support?
Hopsworks supports the following languages:
English
Q. Does Hopsworks support mobile devices?
Hopsworks supports the following devices:
Q. What other apps does Hopsworks integrate with?
Hopsworks integrates with the following applications:
Amazon EC2, Microsoft Azure
Q. What level of support does Hopsworks offer?
Hopsworks offers the following support options:
Email/Help Desk, Knowledge Base, Phone Support, Chat
Related categories
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