MacBook Neo Takes on Cloud Solutions with Enhanced Memory
ClickBench comprises 43 queries geared toward aggregation and filtering tasks, working with a single expansive table containing 100 million rows. This setup demands around 14 GB when saved in Parquet format, raising to 75 GB if using CSV.
On the other hand, TPC-DS consists of 24 tables with 99 diverse queries, many of which incorporate intricate functions.
- c6a.4xlarge, which boasts 16 AMD EPYC vCPU cores and 32 GB of RAM.
- c8g.metal-48xl, equipped with an impressive 192 Graviton4 vCPU cores and 384 GB of RAM.
In the cold run scenario, the MacBook Neo outperformed both cloud servers, completing all queries in under a minute—up to 2.8 times faster than the competition.
It’s essential to note that cloud options utilize network-attached disks, which can slow down database access significantly. Conversely, the MacBook Neo benefits from a local NVMe SSD, providing quicker first-read access.
Moving to the hot run tests, results showed the c8g.metal-48xl triumphed with a swift 4.35 seconds, followed by the c6a.4xlarge at 47.86 seconds, while the MacBook Neo finished at 54.27 seconds—approximately 10% quicker than during its cold run.
Importantly, the MacBook Neo remained competitive against the c6a.4xlarge, completing tasks about 13% slower despite the cloud server’s significant advantage in CPU threads and memory.
At the SF100 level, the laptop navigated the majority of queries with a median response time of 1.63 seconds, wrapping up testing in approximately 15.5 minutes. However, at SF300, some queries consumed up to 80 GB for disk overflow, resulting in extended processing times.
Key Takeaways
- A practical performance evaluation reveals that the MacBook Neo competes well against high-memory cloud servers.
- Cold run tests highlight the advantages of local SSD access.
- Hot run performance shows that powerful cloud configurations can outperform budget laptops.
- Median query performance suggests that the MacBook can be a viable option for certain database tasks.
- The exploration of hardware limitations invites deeper consideration of trade-offs between local and cloud-based computing solutions.