TreeCat: Standalone Catalog Engine for Large Data Systems
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2025
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866916885953511424 |
|---|---|
| author | Oh, Keonwoo Nilangekar, Pooja Deshpande, Amol |
| author_facet | Oh, Keonwoo Nilangekar, Pooja Deshpande, Amol |
| contents | With ever-increasing volume and heterogeneity of data, advent of new specialized compute engines, and demand for complex use cases, large-scale data systems require a performant catalog system that can satisfy diverse needs. We argue that existing solutions, including recent lakehouse storage formats, have fundamental limitations and that there is a strong motivation for a specialized database engine, dedicated to serve as the catalog. We present the design and implementation of TreeCat, a database engine that features a hierarchical data model with a path-based query language, a storage format optimized for efficient range queries and versioning, and a correlated scan operation that enables fast query execution. A key performance challenge is supporting concurrent read and write operations from many different clients while providing strict consistency guarantees. To this end, we present a novel MVOCC (multi-versioned optimistic concurrency control) protocol that guarantees serializable isolation. We conduct a comprehensive experimental evaluation comparing our concurrency control scheme with prior techniques, and evaluating our overall system against Hive Metastore, Delta Lake, and Iceberg. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_02956 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | TreeCat: Standalone Catalog Engine for Large Data Systems Oh, Keonwoo Nilangekar, Pooja Deshpande, Amol Databases With ever-increasing volume and heterogeneity of data, advent of new specialized compute engines, and demand for complex use cases, large-scale data systems require a performant catalog system that can satisfy diverse needs. We argue that existing solutions, including recent lakehouse storage formats, have fundamental limitations and that there is a strong motivation for a specialized database engine, dedicated to serve as the catalog. We present the design and implementation of TreeCat, a database engine that features a hierarchical data model with a path-based query language, a storage format optimized for efficient range queries and versioning, and a correlated scan operation that enables fast query execution. A key performance challenge is supporting concurrent read and write operations from many different clients while providing strict consistency guarantees. To this end, we present a novel MVOCC (multi-versioned optimistic concurrency control) protocol that guarantees serializable isolation. We conduct a comprehensive experimental evaluation comparing our concurrency control scheme with prior techniques, and evaluating our overall system against Hive Metastore, Delta Lake, and Iceberg. |
| title | TreeCat: Standalone Catalog Engine for Large Data Systems |
| topic | Databases |
| url | https://arxiv.org/abs/2503.02956 |