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In Lioran S3’s reported design, RocksDB stores metadata and application state; the filesystem stores object payload bytes. That division keeps database lookups focused on records such as bucket and object mappings, while file paths hold the contents being uploaded or downloaded. The details below describe a V1 pre-alpha implementation, not a production guarantee.
What RocksDB stores—and what it does not
RocksDB is the metadata plane, not the object-content store. Swaraj Puppalwar, Founder & CTO of Lioran Group and Lioran Developer Solutions, states in the project’s architecture article: “Object payload/image bytes are NEVER written to RocksDB.” Instead, the filesystem holds payloads, while RocksDB tracks the information the service needs to identify and manage them.
That metadata includes associations between buckets and logical object keys, as well as state for users, access keys, uploads, indexes, and media-related work. The project describes database lookups and iteration for metadata alongside filesystem streaming and range-oriented I/O for object data.
How logical object names map to files
A client-facing object name and the file that physically contains its bytes belong to separate namespaces. The project article gives bucket/key as an illustrative logical key encoding; it describes the payload’s physical filename as an internal UUID path. The database can therefore associate a bucket and key with an object record without using the client’s name as the payload’s physical path.
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This arrangement separates two kinds of work: RocksDB resolves and iterates records, while file I/O handles the larger payload stream. It explains the division of labor, but by itself does not establish durability or crash-consistency guarantees.
Which metadata families the project reports
The project describes a metadata crate with a MetadataStore abstraction, allowing higher layers to depend on a trait rather than directly on the RocksDB implementation. In addition to RocksDB’s default family, the article reports these column families:
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- Users and access keys
- Buckets and objects
- Uploads
- Video jobs, video shares, and video manifests
- System records
These are the families named in the project article; they should not be treated as a stable external schema or as a complete description of every internal record.
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The October 1, 2026 project article reports the following implementation settings. They describe configuration, not measured throughput, latency, or recommended defaults.
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| Setting | Reported value | How to read it |
|---|---|---|
| Shared LRU block cache | 64 MiB | Shared cache reported for database block access. |
| WAL retention bound | 256 MiB | Reported bound for retained write-ahead log data. |
bytes_per_sync |
1 MiB | Reported synchronization setting. |
wal_bytes_per_sync |
1 MiB | Reported WAL synchronization setting. |
| Object-family write buffer | 64 MiB | Reported write-buffer size for object metadata. |
| Object-family maximum write buffers | 4 | Reported maximum number of write buffers. |
| Object-family minimum buffers to merge | 2 | Reported merge threshold. |
| Object-family block size | 16 KiB | Reported block size. |
| Object-family Bloom filter | 10-bit | Reported filter configuration. |
| Object-family compression | LZ4 | Reported compression choice. |
The article does not provide a named benchmark result or adoption statistic for this RocksDB implementation. None of these settings, on their own, proves a performance advantage or indicates an optimal configuration.
What the reported PUT lifecycle says
A separate project write-path walkthrough describes a PUT as staging and streaming payload bytes to a file, promoting that file to a permanent path, and then writing final metadata to RocksDB. If the metadata write fails, the walkthrough says the implementation attempts to remove the promoted file.
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This is an account of the described implementation behavior, not proof that every interruption or crash leaves the filesystem and database consistent. The article’s sequence and rollback attempt do not establish what happens in every failure window.
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How to interpret the project’s maturity and API scope
The project’s V1 overview calls Lioran S3 pre-alpha. It describes a native REST API and says the product does not yet provide a drop-in AWS S3 REST compatibility layer. The architecture and configuration above should therefore be read as project-reported design details, not as stable production guarantees or a basis by itself for mission-critical deployment.
How this differs from Apache Ozone’s schema
Apache Ozone is a useful architectural comparison, but it is a separate implementation. Its official RocksDB schema documentation describes RocksDB-backed namespace and supporting metadata, including volumes, buckets, keys, S3-style multipart uploads, snapshots, and tenancy. Ozone uses its own tables and key formats; its schema is not Lioran S3’s.
| Aspect | Lioran S3, as reported | Apache Ozone, as documented |
|---|---|---|
| RocksDB’s role | Metadata and application state; payload bytes reside in filesystem paths. | Namespace and supporting metadata, including multipart-related state; see the official schema documentation. |
| Named metadata entities | Users, access keys, buckets, objects, uploads, video jobs, video shares, video manifests, and system records. | Volumes, buckets, keys, S3-style multipart uploads, snapshots, tenancy, and supporting state. |
| Schema and key format | Project article gives bucket/key as an illustrative logical key encoding and describes a UUID-based physical payload path. |
Ozone-specific tables and key formats. |
The comparison shows a shared architectural use of RocksDB for object-store metadata; it does not make the products’ schemas, API guarantees, or maturity equivalent.
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