Introduction
...
| Info |
|---|
We refer to "document" as a catch all for database record, Web page, PDF/office document, XML document etc. The figures below are for some "average" document across all those types ... if most documents ingested are smaller (eg DB records) then the capacity/performance will be higher and conversely if most documents are larger (eg large complex pdf reports) then the capacity/performance will be lower. |
Demo configuration
For running in a VM on a laptop to demonstrate the tool. May become slow for more than 100-1000 documents.
| Infinit.e API + DB Node | |
|---|---|
| Processor | 1x 1.8+ GHz CPU |
| Memory | 1 or 2 GB RAM (swap required to get up to ~8GB total) |
| Network | WAN connection/none |
| Storage | 20GB |
Compact configuration
...
| Infinit.e API + DB Node | |
|---|---|
| Processor | 1 X Dual/Quad Core 1.8+ GHz CPUs |
| Memory | 4-8 GB RAM (swap required to get up to ~8GB total) |
| Network | 1x GigE LAN connection |
| Storage | 10 GB Root/OS partition + |
...
| Infinit.e API Node | Infinit.e Database Node | |
|---|---|---|
| Processor | 1-2 X Dual Core 1.8+ GHz CPUs | 1-2 X Dual Core 1.8+ GHz CPUs |
| Memory | 8-16 GB RAM (or more) | 8-16 GB RAM (or more) |
| Network | 2x GigE LAN connection | 2x GigE LAN connection |
| Storage | 15 GB Root/OS partition + (~5GB per 1 million documents) | 15 GB Root/OS partition + (~10GB per 1 million documents) |
...
| Infinit.e API Node | Infinit.e Database Node | |
|---|---|---|
| Processor | 2 X Dual Core 1.8+ GHz CPUs | 2 X Dual Core 1.8+ GHz CPUs |
| Memory | 16 GB RAM or more (32GB is ideal) | 16 GB RAM or more (32GB is ideal) |
| Network | 2x GigE LAN connection | 2x GigE LAN connection |
| Storage | 20 GB Root/OS partition + | 20 GB Root/OS partition + 100+ GB data partition, RAID-0 (~10GB per 1 million documents) |
...