Highly Scalable Data Service (HSDS)
Highly Scalable Data Service (HSDS): A focused REST service for teams that need parallel access to HDF5 datasets. Ranked #29 of 31 in Cloud File Storage Services by our editors (6.5/10); pricing: Free plan; best for developers managing HDF5 data through a REST API.
At a glance
- Editor score6.5 / 10
- PricingFree plan
- Best forDevelopers managing HDF5 data through a REST API
- Free planYes
- Paid fromFree
- Supported protocolsHTTP, HTTPS, REST
- Facts checked23 Sep 2026
Where it wins
- Reads and writes HDF5 data in object and POSIX storage
- Supports parallel processing and multiple readers and writers
- Offers dataset queries, selection tools, and role-based access controls
Where it doesn't
- Focused on HDF5 data rather than general-purpose file storage
- Deployment uses service and data-node containers, adding operational work
- Support is community-based for the open-source software
Our verdict on Highly Scalable Data Service (HSDS)
Highly Scalable Data Service (HSDS) is an open-source REST service for reading, writing, and sharing HDF5 data in object-storage environments, including cloud and POSIX storage. It is aimed at developers and organizations handling scientific or engineering datasets that need API access and parallel workflows. HDF5 and Python h5py-compatible applications can connect through REST VOL, h5pyd, and command-line tools, making HSDS a fit where those formats and workflows are already central.
Its depth is in data access rather than file management. HSDS supports parallel processing across data nodes, multiple readers and writers, compression, hyperslab and point selection, SQL-like dataset queries, and asynchronous processing. Role-based access control and access-control lists address permissions. Storage options include AWS S3, Azure Blob Storage, MinIO, and POSIX storage; deployments can run in the cloud or self-hosted, using service and data-node containers on one server or across a Kubernetes cluster. Docker is also listed among its integrations. The vendor documents a dynamically changing server-node count, while the published scaling model is auto-scaling.
HSDS itself is open-source software with a free plan. The vendor separately offers paid support, consulting, and managed offerings, so teams should distinguish those from the software. Community support is the listed support channel for HSDS. Choose it when REST access to HDF5 data, parallel reads and writes, and dataset queries are core needs; teams looking for a general-purpose cloud file-storage service should choose a broader storage product instead. Deployment and operations also make it a less direct fit for teams seeking a turnkey file-sharing service.
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Highly Scalable Data Service (HSDS) pricing
Highly Scalable Data Service (HSDS) fact sheet
| Free plan | Yes |
|---|---|
| Paid from | Free |
| Supported protocols | HTTP, HTTPS, REST |
| Maximum capacity | Not verified |
| Availability zones | Not verified |
| Snapshots | Not verified |
| Managed backups | Not verified |
| Scaling model | Auto_scaling |
| Deployment | Cloud, Self-hosted |
| Platforms | Web, Linux |
| Support | Community |
| Built for | Small business, Mid-market, Enterprise (editorial estimate) |
| Integrations | 6 integrations: AWS S3, Azure Blob Storage, MinIO, POSIX storage, Kubernetes, Docker |
| Pricing | Free plan |
| Website | hdfgroup.org |
| Facts checked | 23 Sep 2026 |
Highly Scalable Data Service (HSDS) integrations
Highly Scalable Data Service (HSDS) lists 6 integrations on its own site.
- AWS S3
- Azure Blob Storage
- MinIO
- POSIX storage
- Kubernetes
- Docker
Alternatives to Highly Scalable Data Service (HSDS)
- Amazon FSx for NetApp ONTAPA broad AWS storage service for enterprise file and block workloads.9.4
- Alibaba Cloud File Storage NASFlexible NFS and SMB file storage for Alibaba Cloud workloads, with usage-based tiers.9.3
- NetApp Cloud Volumes ONTAPA broad ONTAP storage appliance for enterprise workloads across AWS, Azure, and Google Cloud.9.2
See all Highly Scalable Data Service (HSDS) alternatives →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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