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Description
Information such as instrument configurations, the most recent service date, the analyst's identity, and the duration of the experiment is currently not recorded. This results in the loss of raw data, making it nearly impossible to alter or rerun analyses without significant effort, and the absence of traceability complicates meta-analyses. The process of simply entering primary analysis outcomes can become a burden that hinders scientists’ efficiency. However, by storing raw data in the cloud and automating the analytical processes, we ensure traceability throughout. Subsequently, this data can be integrated into various platforms such as ELNs, LIMS, Excel, analysis applications, and pipelines. Moreover, we continuously develop a data lake that accumulates all this information. This means that all your raw data, processed results, metadata, and even the internal data from connected applications are securely preserved forever within a unified cloud data lake. Analyses can be executed automatically, and metadata can be appended without manual input. Additionally, results can be seamlessly transmitted to any application or pipeline, and even back to the instruments for enhanced control, thereby streamlining the entire research process. This innovative approach not only increases efficiency but also significantly improves data management.
Description
lakeFS allows you to control your data lake similarly to how you manage your source code, facilitating parallel pipelines for experimentation as well as continuous integration and deployment for your data. This platform streamlines the workflows of engineers, data scientists, and analysts who are driving innovation through data. As an open-source solution, lakeFS enhances the resilience and manageability of object-storage-based data lakes. With lakeFS, you can execute reliable, atomic, and versioned operations on your data lake, encompassing everything from intricate ETL processes to advanced data science and analytics tasks. It is compatible with major cloud storage options, including AWS S3, Azure Blob Storage, and Google Cloud Storage (GCS). Furthermore, lakeFS seamlessly integrates with a variety of modern data frameworks such as Spark, Hive, AWS Athena, and Presto, thanks to its API compatibility with S3. The platform features a Git-like model for branching and committing that can efficiently scale to handle exabytes of data while leveraging the storage capabilities of S3, GCS, or Azure Blob. In addition, lakeFS empowers teams to collaborate more effectively by allowing multiple users to work on the same dataset without conflicts, making it an invaluable tool for data-driven organizations.
API Access
Has API
API Access
Has API
Integrations
Amazon Athena
Amazon Kinesis
Amazon S3
Amazon SES
Apache Airflow
Apache Flink
Apache Hive
Apache Spark
Astro by Astronomer
Azure Blob Storage
Integrations
Amazon Athena
Amazon Kinesis
Amazon S3
Amazon SES
Apache Airflow
Apache Flink
Apache Hive
Apache Spark
Astro by Astronomer
Azure Blob Storage
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Ganymede
Country
United States
Website
www.ganymede.bio/
Vendor Details
Company Name
Treeverse
Founded
2020
Country
Israel
Website
lakefs.io
Product Features
Medical Lab
Audit Trail
Data Analysis Auditing
Data Security
EMR Interface
Fax Management
Lab Instrument Interface
Multi-Location Printing
Online Instrumentation
Physician Test Panels
Procedure-Based Billing
Sample Tracking
Product Features
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge