Enables realtime data processing.

Provides faulttolerance and high availability.

Drag and drop user interface

Visualizes data flows in realtime

Enables easy debugging and troubleshooting

Built to address limitations of Hive and HDFS

Provides ACID transactions, schema evolution, and partitioning

Allows for querying across multiple tools

Allows for easy table discovery and organization

Supports searching and filtering of table metadata

Including HDFS, S3, and GCS

Designed to run on commodity hardware

Provides high throughput access to data

Scales horizontally

It is open source and allows for scalable storage.

It is compatible with Amazon S3 API.

It offers various features such as bucket policies and versioning.

This includes Kubernetes, Docker, and Terraform.

Integration with these tools makes it easy to deploy and manage Minio.

Spark is fast and scalable.

Workflow management system

from various sources

supports metadata models

metadata search

metadata editing

metadata versioning

metadata access control

Integrates with Hadoop ecosystem (HDFS, Hive, HBase, Kafka, Spark, etc.)

Classification, Glossary, Lineage, Discovery, Search, etc.

Allows custom metadata types and attributes

Data classification and labeling

Data retention and expiration

Data lineage and traceability

Centralized metadata repository

Automated metadata capture and ingestion

Metadata versioning and history tracking

Export and import of metadata