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---
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icon: material/memory
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title: "Triple Store Sizing"
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---
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# Triple Store Sizing
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The following table provides a generic sizing orientation when planning the triple store hardware.
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## Sizing Factors
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The actual hardware requirements depend on several factors, including:
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- **Data Model Complexity**: The number of statements and the complexity of the ontology.
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- **Workload**: The types of queries (e.g., analytical vs. transactional) and update frequency.
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- **Users**: The number of concurrent users and their usage patterns.
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- **Hardware**: The specific performance characteristics of the server hardware (CPU, Disk, RAM).
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## Sizing Table
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| Statements | RAM | Disk Usage |
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| ---: | ---: | ---: |
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| ~130 M | 8 GB | ~15 GB |
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| ~280 M | 16 GB | ~32 GB |
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| ~1.100 M | 32 GB | ~110 GB |
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| ~2.500 M | 64 GB | ~290 GB |
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| ~20.000 M | 128 GB | ~2.000 GB |
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## Performance Considerations
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When planning your infrastructure, consider the following performance priorities:
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- **CPU**: Single-core performance is critical for query execution speed.
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- **Disk I/O**: High IOPS and throughput are essential for load and indexing performance. SSDs are strongly recommended.
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- **RAM**: While CPU and Disk influence performance, RAM is the mostly limiting factor in terms of the maximum amount of triples that can be loaded and queried efficiently.

docs/develop/python-plugins/setup/index.md

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An installation of the CPython distribution (at least version 3.3) is required.
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Although other distributions, such as Anaconda, should work as well, only CPython is officially supported.
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The official image ships with a tested python interpreter (currently - 2024 - Python 3.11).
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The official image ships with a tested python interpreter (currently - 2025 - Python 3.13).
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??? note "Java Embedded Python (Jep)"
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