12 Best laptops for Big Data in 2023

As someone who has spent a significant amount of time exploring the world of big data, I understand that finding the best laptop for big data professionals is crucial to making your work more efficient and enjoyable. From processing massive datasets to running complex data analytics tools, the ideal laptop must possess the power and capabilities to manage these tasks without breaking a sweat. In this guide, I'll help you navigate the sea of options to find the perfect laptop tailored to your big data needs.

To create this guide, I've reviewed an extensive spreadsheet of recent laptop releases, comparing specs and reviews from both professionals and users. Through this process, I've identified the top laptops based on the specific requirements of big data professionals and a range of price points. Among the factors I've considered are processing power, memory capacity, storage solutions, and GPU performance, as these are all critical in handling large datasets, running data-intensive applications, and even visualizing your findings.

As a big data enthusiast, I know that a high-performance laptop can make all the difference in streamlining your workflows and tackling complex data challenges. Whether you're working with Hadoop, Spark, or other big data frameworks, this guide will provide you with the insights needed to make an informed decision on the best laptop for big data tasks. Say goodbye to sluggish performance and hello to a seamless big data experience.

Table of Contents

Processing Power: The Backbone of Big Data Laptops

If you're in the market for a laptop to handle Big Data workloads, the right processor can make all the difference. Let's take a look at the latest processor offerings from Intel and AMD and how they stack up for Big Data applications.

What's new in the processor market?

Intel's 13th-generation Core processors have already been released, but their 12th-generation CPUs still provide excellent value, especially for those not needing cutting-edge performance. AMD has also made strides in the laptop CPU market, capturing 20% of the market share with its 6th and 7th-generation Ryzen processors. Apple's ARM-based M1, M2, M2 Pro, and M2 Max system-on-chip modules offer exceptional single-core performance and battery life, but we can ignore them for cross-platform Big Data applications.

How much money do you have for a processor?

Deciding on a budget is a crucial first step. If you're on a tight budget, an i3-1115G4 can handle basic Big Data workloads. Still, if you can afford it, an i5-1135G7 or Ryzen 5/7 would be a nice upgrade. If money is no object, an i7-11370H provides excellent performance for demanding applications.

What are your workloads?

For Hadoop or Spark applications, you don't need a high-end processor. An 8th or 9th-generation Core i5/i7 or Ryzen 5/7 will do the job just fine. However, if you're working with large datasets, machine learning algorithms, or other demanding applications, investing in a faster CPU can significantly reduce processing times.

Is it worth investing in a fast CPU for data science?

It depends on your specific workloads. Suppose you're working with large datasets or machine learning algorithms. In that case, a faster CPU can significantly reduce processing times and improve productivity. On the other hand, if you're working with smaller datasets or less demanding applications, a mid-range CPU will suffice.

Recommended processors by price range

Here are our recommendations for processors based on price range:

Processor	Price Range	PassMark Score	Cinebench R23 Score
i3-1115G4	Under $500	5126	1047
i5-1135G7	$500-$1000	10270	2656
Ryzen 5/7	$500-$1000	12500	2875
i7-11370H	Over $1000	12606	3304

Remember, when selecting a laptop for Big Data workloads, you'll also want to consider factors such as RAM and storage. A minimum of 16GB of RAM and 500GB of SSD storage is recommended for optimal performance.

Graphics Matter: What to Consider When Choosing a Laptop for Big Data Processing

In recent years, there have been significant changes in the laptop GPU market. Nvidia continues to dominate, with the RTX 30 series cards being the most popular choice for current notebook GPUs. However, the recently released RTX 40 series cards are also hitting the market.

For Big Data jobs, a dedicated GPU is not necessary but can provide a performance boost in certain situations such as training deep learning models or performing fast matrix operations. In terms of ranking GPUs for data science applications, I use 3DMark since it's the most popular option for data scientists. However, for an all-around laptop that can handle both data science and gaming, other benchmarks like 3DMark Advanced or Unigine Heaven/Valley benchmarks can be considered.

When selecting a laptop GPU for Big Data tasks, consider the following factors:

The budget you have.
The tasks you will be performing.
The balance between power and portability.

Here are some recommended GPUs for different price ranges:

GPU	Price
GeForce GTX 1650	$500 – $800
GeForce RTX 3050	$800 – $1,200
GeForce RTX 2060	$1,200 – $1,800

Keep in mind that laptop manufacturers determine the exact GPU wattage, so there may be a wide variance in graphics performance, even with laptops having the same GPU chipset.

RAM it up: How much memory do you need?

RAM, or Random Access Memory, plays a crucial role in Big Data applications, which are often memory-hungry by nature. While most mid-range laptops come with 16 GB of RAM and high-end laptops with 32 GB or more, Big Data professionals need to make sure they have enough RAM to handle their workload.

For most Big Data use cases, 16 GB is the bare minimum, while 32 GB is ideal for anything that requires a lot of data analysis. However, if you're working with HPC applications or machine learning models, you should aim for 64 GB or more.

It's worth noting that while some laptops allow RAM upgrades, most come with soldered RAM and cannot be upgraded after purchase. If you think you might need more RAM down the line, make sure to buy a laptop with upgradable RAM and an upgradeable SODIMM slot.

As for DDR5, while it does offer better performance than DDR4, it's still quite expensive and needs time to mature as a technology. If you're looking for a laptop that can handle multiple data science projects at once, consider getting one with DDR5 RAM. However, DDR4 RAM is still perfectly suitable for most Big Data applications.

Other considerations when choosing laptop RAM include ECC (Error-Correcting Code) for data integrity, CL (CAS Latency) for speed, and frequency for overall performance. However, these factors may not be as important as the amount of RAM you have for most Big Data applications.

Here are some recommendations for laptop RAM based on various price levels:

Price Range	RAM Recommendation
Under $500	8 GB
$500-$1000	16 GB
$1000 and up	32 GB or more

In summary, when choosing the right laptop RAM for Big Data, make sure to consider the amount of RAM needed for your workload, the possibility of upgrading RAM in the future, and whether DDR5 is worth the extra cost. With these factors in mind, you can make an informed decision and choose a laptop that will meet your Big Data needs.

Unraveling the Mysteries of Big Data Laptop Buying

Q: What is the best laptop for Big Data?

The best laptop for Big Data depends on your budget and specific needs. However, we recommend the MSI Summit E13 or Lenovo Legion 5 Pro for their powerful processors and high-end graphics cards, making them perfect for heavy data processing and visualization.

What specs are needed for a Big Data laptop?

A Big Data laptop should have a minimum of 8 GB of RAM, an i5-1135G7 or better processor, and a GeForce GTX 1650 or better graphics card. However, for optimal performance, we recommend 16 GB of RAM, an i7-11370H or better processor, and a GeForce RTX 3050 or better graphics card.

Can a laptop handle Big Data processing?

Yes, laptops can handle Big Data processing, but it depends on the laptop's specifications. Laptops with high-end processors, graphics cards, and sufficient RAM can handle Big Data processing with ease.

How much RAM is required for Big Data on a laptop?

A minimum of 8 GB of RAM is required for Big Data processing on a laptop. However, we recommend 16 GB or 32 GB of RAM for optimal performance, depending on your budget and specific needs.

Which processor is best for Big Data analysis on a laptop?

The i7-11370H or better processor is best for Big Data analysis on a laptop. It offers excellent performance and can handle heavy data processing with ease.

What graphics card is required for Big Data visualization on a laptop?

A GeForce RTX 3050 or better graphics card is required for Big Data visualization on a laptop. The RTX 3050 offers excellent graphics performance, which is ideal for visualizing complex data.

Can a budget laptop be used for Big Data analysis?

Yes, a budget laptop can be used for Big Data analysis. However, you may need to compromise on performance and specifications. We recommend considering the ASUS Zenbook or GIGABYTE AORUS 15 XE4 as budget-friendly options with decent specs.

Is SSD storage necessary for a Big Data laptop?

SSD storage is not necessary, but it can significantly improve the performance of a Big Data laptop. If you have the budget, we recommend opting for an SSD, as it offers faster read and write speeds, which is ideal for working with large datasets.

How to choose a laptop for Big Data processing?

When choosing a laptop for Big Data processing, consider the following factors: RAM, processor, graphics card, storage, and budget. Opt for at least 16 GB of RAM, an i7 processor, a powerful graphics card, SSD storage (if possible), and a budget of at least $1,000.

Can I use a gaming laptop for Big Data analysis?

Yes, gaming laptops can be used for Big Data analysis. Gaming laptops typically have powerful processors and high-end graphics cards, making them well-suited for handling large datasets. However, be sure to check the specifications before making a purchase. The ASUS ROG Strix Scar is a good option for those seeking a high-performance gaming laptop for Big Data analysis.

6 Best Laptops for Big Data

$640

1.ASUS Zenbook

ASUS Zenbook is a powerful and compact laptop for big data analysis.

Pros

Excellent battery life
Compact dimensions and low weight
Fast processor and sleek design
Bright display

Cons

Soldered RAM that cant be expanded
Fan behavior annoying at times and high emissions under load
Weak Wi-Fi
Only a few ports.

View on Amazon

Summary

ASUS Zenbook is a lightweight, powerful laptop with a long battery life and fast processor, perfect for big data analysis. Its sleek design and bright display are great, but the soldered RAM, weak Wi-Fi, and high emissions under load are some cons to consider.

Reviews

Notebookcheck

83%/100

Asus ZenBook 14 UM425U [5700U version]

Ultrabookreview

4.5/5

Asus ZenBook 14 UM425QA [5800H version]

Alternatives

$710

HP Victus 15

Pros

Strong gaming performance for its price
Solid productivity performance

Cons

Display and webcam could be better
Too much pre-installed software

$880

2.HP Victus 15

HP Victus 15: A budget laptop that can handle light gaming and work tasks.

Pros

Affordable price
Good gaming performance for the price range
Can double as a work laptop
Multiple color choices

Cons

Short battery life
Plain design
Weak GPU yields unsatisfactory frame rates
Screen only so-so despite 144Hz refresh rate

View on Amazon