# [Accelerate search performance with SVE2 MATCH on Arm servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/sve2-match/)

## In this learning path

- [Introduction](https://learn.arm.com/learning-paths/servers-and-cloud-computing/sve2-match/)
- [Compare search performance using scalar and SVE2 MATCH on Arm Servers](https://learn.arm.com/learning-paths/servers-and-cloud-computing/sve2-match/sve2-match-search/)
- [Next Steps](https://learn.arm.com/learning-paths/servers-and-cloud-computing/sve2-match/_next-steps/)

## About this Learning Path

| Skill level:     | Introductory             |
|------------------|--------------------------|
| Reading time:    | 20 min                   |
| Last updated:    | 31 Jul 2026              |

| Author:          | Pareena Verma, Arm [GitHub](https://github.com/pareenaverma) [LinkedIn](https://linkedin.com/in/pareena-verma-7853607) |
|------------------|--------------------------|
| Arm IP:          | [Neoverse](https://support.arm.com/?tab=compute-ip&Product%20Type=Infrastructure%20Processors)                       |
| Tags:            | [Performance and Architecture](https://learn.arm.com/tag/performance-and-architecture), [AWS](https://learn.arm.com/tag/aws), [Microsoft Azure](https://learn.arm.com/tag/microsoft-azure), [Google Cloud](https://learn.arm.com/tag/google-cloud), [Linux](https://learn.arm.com/tag/linux), [SVE2](https://learn.arm.com/tag/sve2), [Neon](https://learn.arm.com/tag/neon), [Runbook](https://learn.arm.com/tag/runbook) |

### Who is this for?
This is an introductory topic for database developers, performance engineers, and anyone optimizing data processing workloads on Arm-based cloud instances.

### What will you learn?
Upon completion of this Learning Path, you will be able to:
- Understand the purpose and function of SVE2 MATCH instructions.
- Implement a search algorithm using both scalar and SVE2-based MATCH approaches.
- Benchmark and compare performance between scalar and vectorized implementations.
- Analyze speedups and efficiency gains on Arm Neoverse-based instances with SVE2.

### Prerequisites
Before starting, you will need the following:
- Access to an [AWS Graviton4, Google Axion, or Azure Cobalt 100 virtual machine](https://learn.arm.com/learning-paths/servers-and-cloud-computing/csp/) from a cloud service provider.