In an interesting test, DuckDB’s Gábor Szárnyas compared the 512GB MacBook Neo with a range of cloud servers to see how Apple’s new entry-level laptop performs on heavy database workloads. Here’s how it did.
MacBook Neo goes up against cloud servers with up to 4× more memory
In a blog post titled Big Data on the Cheapest MacBook (via Boing Boing), Szárnyas describes how he benchmarked the MacBook Neo using two benchmarks: ClickBench and TPC-DS:
ClickBench has 43 queries that focus on aggregation and filtering operations. The operations run on a single wide table with 100M rows, which uses about 14 GB when serialized to Parquet and 75 GB when stored in CSV format.
TPC-DS has 24 tables and 99 queries, many of which are more complex and include features such as window functions. And while TPC-H has been optimized to death, there is still some semblance of value in TPC-DS results.
In all tests, the MacBook Neo was up against two cloud instances:
- c6a.4xlarge with 16 AMD EPYC vCPU cores and 32 GB RAM.
- c8g.metal-48xl with a whopping 192 Graviton4 vCPU cores and 384 GB RAM.
For the ClickBench benchmark, they ran two tests: a cold run, which measures performance when caches are empty, and a hot run, which measures performance once the system can take advantage of caching.
For the cold run, the MacBook Neo beat both cloud instances by quite a lot, completing all queries under a minute, up to 2.8 times faster than its counterparts.
While impressive, DuckDB explains that:
Of course, if we dig deeper into the setups, there is an explanation for this. The cloud instances have network-attached disks, and accessing the database on these dominates the overall query runtimes. The MacBook Neo has a local NVMe SSD, which is far from best-in-class, but still provides relatively quick access on the first read.
Things took a turn during the hot run test: c8g.metal-48xl completed the run in 4.35 seconds, c6a.4xlarge came in as a distant runner-up at 47.86 seconds, and the MacBook Neo finished last at 54.27 seconds, roughly 10% faster than in the cold run.
However, it’s worth noting that on median query runtimes the MacBook Neo can still beat the c6a.4xlarge, a mid-sized cloud instance. And the laptop’s total runtime is only about 13% slower despite the cloud box having 10 more CPU threads and 4 times as much RAM.
As for the TCP-DS benchmark, DuckDB offers a bit less comparative detail, but shows that the MacBook Neo still performed quite well, considering its hardware:
At SF100, the laptop breezed through most queries with a median query runtime of 1.63 seconds and a total runtime of 15.5 minutes.
At SF300, the memory constraint started to show. While the median query runtime was still quite good at 6.90 seconds, DuckDB occasionally used up to 80 GB of space for spilling to disk and it was clear that some queries were going to take a long time. Most notably, query 67 took 51 minutes to complete. But hardware and software continued to work together tirelessly, and they ultimately passed the test, completing all queries in 79 minutes.
Interestingly, this wasn’t the first time they tested the A19 Pro chip. Back when the iPhone 16 Pro came out, they ran the TCP-H benchmark with the device inside a bucket of dry ice at -50ºC, where it completed the run in 478.2 seconds.
To learn more about DuckDB’s benchmarks on the MacBook Neo, follow this link.
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