google/tensorstore

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1536 stars · 144 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

TensorStore is a C++ and Python library for reading and writing large multi-dimensional arrays with a uniform API across formats like zarr, N5, and Neuroglancer precomputed. It supports multiple storage backends (local filesystems, Google Cloud Storage, S3), asynchronous high-throughput access, caching, transactions with ACID guarantees, and safe concurrent access from multiple processes and machines.

Use cases

• store and read large multi-dimensional arrays like image volumes or ML datasets
• read and write zarr or N5 arrays from Python
• access chunked array data on S3 or Google Cloud Storage
• process large arrays concurrently from multiple machines safely
• stream large arrays with high throughput over high-latency remote storage
• apply composable indexing and virtual views to array data

When to choose

• you need to store or manipulate very large n-dimensional arrays that exceed memory
• you need a uniform API over multiple array storage formats and backends
• you need transactional, consistent concurrent access to array data across processes or machines
• you work in scientific computing, neuroimaging, or ML data pipelines with chunked array storage

When to avoid

• you only need small in-memory arrays handled by NumPy or PyTorch tensors
• you need a general-purpose relational or document database
• you need tabular or dataframe storage rather than multi-dimensional arrays
• you need a simple key-value store without array semantics

Facets

library · maturity active

database-driver serialization file-system caching concurrency data-science machine-learning big-data developer-tools cpp python windows cross-platform multi-dimensional-arrays zarr n5 tensor-storage object-storage acid-transactions scientific-computing data-engineering linux macos

Member repositories

For agents

markdown · JSON · MCP: product_card(name="google/tensorstore")