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.

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

Ryzen 5 5500U | MX450 | 8 GB RAM | 512 GB SSD | 14″ IPS; 1920x1080 |

1.ASUS Zenbook

ASUS Zenbook is a powerful and compact laptop for big data analysis.
  • Excellent battery life
  • Compact dimensions and low weight
  • Fast processor and sleek design
  • Bright display
  • Soldered RAM that cant be expanded
  • Fan behavior annoying at times and high emissions under load
  • Weak Wi-Fi
  • Only a few ports.

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.

HP Victus 15
  • Strong gaming performance for its price
  • Solid productivity performance
  • Display and webcam could be better
  • Too much pre-installed software
i5-12450H | GTX 1650 | 32 GB RAM | 2000 GB SSD | 15.6″ IPS WA; 1920x1080 |

2.HP Victus 15

HP Victus 15: A budget laptop that can handle light gaming and work tasks.
  • Affordable price
  • Good gaming performance for the price range
  • Can double as a work laptop
  • Multiple color choices
  • Short battery life
  • Plain design
  • Weak GPU yields unsatisfactory frame rates
  • Screen only so-so despite 144Hz refresh rate

The HP Victus 15 is a budget-friendly laptop suitable for those looking for an affordable device that can handle both light gaming and work tasks. However, its plain design and poor battery life may turn off some users.

HP Victus 15
MSI Summit E13
  • Large battery with respectable runtimes
  • Great CPU and GPU performance
  • Slow display response times and noticeable ghosting
  • High core temperatures when under load
Ryzen 7 6800H | RTX 3060 | 32 GB RAM | 2000 GB SSD | 16″ IPS HDR G-Sync; 2560x1600 |

3.Lenovo Legion 5 Pro

Lenovo Legion 5 Pro is a powerful machine for Big Data at a reasonable price.
  • High quality 165 Hz 16:10 IPS display
  • Relatively easy serviceability
  • Integrated numpad
  • Very fast charging
  • Low resolution webcam with no IR or privacy shutter
  • Very warm CPUGPU temperatures when gaming
  • Moderate-heavy uneven backlight bleeding
  • Only average battery life

Lenovo Legion 5 Pro is a big upgrade from its predecessor with an AMD Zen 3+ CPU, 150W TGP GPU, and a 165 Hz 16:10 IPS display. The laptop has relatively easy serviceability and very fast charging.

  • Faster than most other GeForce RTX 3060 laptops
  • 300 Hz IPS panel w full sRGB coverage
    i7-12700H | RTX 3070 Ti | 64 GB RAM | 2000 GB SSD | 15.6″ IPS-level; 2560x1440 |


    GIGABYTE AORUS 15 XE4 is a top-performing laptop, but with high power usage.
    • Highly responsive 165Hz panel and wide color gamut
    • High system performance with PCIe 4.0 SSD and free M.2 2280 slot
    • Individual key lighting, Thunderbolt 4, and Power Delivery
    • Solid battery life
    • High power usage at idle and

    GIGABYTE AORUS 15 XE4 is a high-performing compact gaming laptop with a wide color gamut and 165Hz panel, ideal for gaming and non-gaming applications. It comes with PCIe 4.0 SSD and a free M.2 2280 slot, individual key lighting, Thunderbolt 4, and Power Delivery. However, it has high power usage at idle and low load, only one USB-A port, and no card reader.

    ASUS ROG Strix G15 G513RM
    • Punchy and fast QHD 240 Hz screen
    • Fair design and solid build quality
    • High CPU and GPU temperatures with games demanding loads
    • No ThunderboltUSB 4, card-reader, camera or biometrics
    Ryzen 9 5900HX | RTX 3080 | 64 GB RAM | 4000 GB SSD | 15.6″ IPS-level G-Sync; 1920x1080 |

    5.ASUS ROG Strix Scar

    ASUS ROG Strix Scar: A powerful laptop for gaming and data analysis, but with thermal issues.
    • High performance for gaming and data analysis
    • Sturdy build quality
    • Fast Wi-Fi 6E connectivity
    • Excellent display with wide color gamut and no PWM
    • High heat and noise emissions under load
    • Limited display angle
    • Heavy SSD throttling during continuous reads
    • No biometric login

    The ASUS ROG Strix Scar is a great choice for gamers and data analysts alike, thanks to its Core i9-12900H processor and RTX 3070 Ti graphics card. However, it can get quite hot and noisy under load, and the battery life is average.

    Acer Predator Triton 500
    • High-performance capabilities
    • Excellent, bright 240-Hz display
    • Soldered-in RAM
    • Inaccessible SSD
    i9-12900HK | RTX 3060 | 32 GB RAM | 6000 GB SSD | 17.3″ IPS HDR; 3840x2400 |

    6.Dell XPS 17 9720

    Dell XPS 17 9720 is a high-performance laptop with a beautiful display, but lacking in graphics and cooling.
    • Excellent 4K display with AdobeRGB
    • High-quality case
    • Thunderbolt 4 PCIe 4.0 for fast data transfer
    • Very high system performance
    • Lower graphics performance than the predecessor
    • Performance not completely stable under combined load
    • Not Wi-Fi 6E compatible
    • 720p webcam

    The Dell XPS 17 9720 is a powerful laptop that boasts an excellent 4K display with AdobeRGB and high-quality case, but it falls short in terms of graphics performance and cooling. It's a great machine for general use, but not the best option for gaming or heavy workloads.

    Dell XPS 17 9720 review
    ASUS ROG Zephyrus Duo
    • Dual-screen setup
    • Powerful gaming performance
    • High cost
    • Awkward keyboard and touchpad layout

    Table of the Best Laptops for Big Data

    LaptopPrice (approx)
    ASUS Zenbook$640
    HP Victus 15$880
    Lenovo Legion 5 Pro$1,350
    GIGABYTE AORUS 15 XE4$1,600
    ASUS ROG Strix Scar$2,310
    Dell XPS 17 9720$5,600
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    John Winstler
    With over a decade of experience in the tech industry, combined with a degree in computer science, I have developed an in-depth knowledge of laptops, PC games, software, 3D modeling, video editing, and photo editing. My detailed and unbiased laptop reviews have helped many people make informed decisions about their technology purchases.

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