// SOLUTIONS / DATA PREPARATION
Data Preparation
Collect your data, store, label and visualize it using our sets of tools and services built for ML data pipelines.
Scalable object storage
S3-compatible object storage for petabyte-scale datasets with high throughput for parallel data loading.
Managed Apache Spark
Process and transform large datasets with managed Spark clusters. No infrastructure management required.
Data versioning
Track dataset versions alongside model experiments using DVC integration with our object storage.
Managed PostgreSQL
Reliable, fully managed PostgreSQL for metadata storage, feature stores, and structured data management.
Build your complete ML data pipeline
From raw data ingestion to cleaned, labeled training datasets — our platform provides the storage, compute, and managed services to build robust data pipelines.
Combine object storage for raw data, Spark for transformations, PostgreSQL for metadata, and shared filesystem for training-ready datasets — all within the same cloud environment as your GPUs.
Essential resources
Object Storage
S3-compatible storage for datasets, models, and artifacts at any scale.
Managed Spark
Process terabytes of data with zero-maintenance Apache Spark clusters.
Managed PostgreSQL
Fully managed PostgreSQL for metadata, feature stores, and structured data.
Shared Filesystem
High-performance shared storage accessible from all nodes in your cluster.
Compatible tools
DVC
Data Version Control for tracking datasets and ML artifacts alongside your code.
Label Studio
Open-source data labeling platform for text, images, audio, and video annotation tasks.
Great Expectations
Data quality framework for validating, documenting, and profiling your data pipelines.