Hardware Guide

The Hardware Guide describes the SQreamDB reference architecture, emphasizing the benefits to the technical audience, and provides guidance for end-users on selecting the right configuration for a SQreamDB installation.

Need help?

This page is intended as a “reference” to suggested hardware. However, different workloads require different solution sizes. SQreamDB’s experienced customer support has the experience to advise on these matters to ensure the best experience.

Visit SQreamDB’s support portal for additional support.

Cluster Architectures

SQreamDB recommends rackmount servers by server manufacturers Dell, Lenovo, HP, Cisco, Supermicro, IBM, and others.

A typical SQreamDB cluster includes one or more nodes, consisting of:

  • Two-socket enterprise processors, such as Intel® Xeon® Gold processors or the IBM® POWER9 processors, providing the high performance required for compute-bound database workloads.

  • NVIDIA Tesla GPU accelerators, with up to 5,120 CUDA and Tensor cores, running on PCIe or fast NVLINK busses, delivering high core count, and high-throughput performance on massive datasets.

  • High density chassis design, offering between 2 and 4 GPUs in a 1U, 2U, or 3U package, for best-in-class performance per cm2.

Single-Node Cluster

A single-node SQreamDB cluster can handle between 1 and 8 concurrent users, with up to 1PB of data storage (when connected via NAS).

An average single-node cluster can be a rackmount server or workstation, containing the following components:

Component

Type

Server

Dell R750, Dell R940xa, HP ProLiant DL380 Gen10 or similar (Intel only)

Processors

2x Intel Xeon Gold 6348 (28C/56HT) 3.5GHz or similar

RAM

1.5 TB

Onboard storage

  • 2x 960GB SSD 2.5in hot plug for OS, RAID1

  • 2x 2TB SSD or NVMe, for temporary spooling, RAID0

  • 10x 3.84TB SSD 2.5in Hot plug for storage, RAID6

GPU

NVIDIA 2x A100, H100, or L40S

Operating System

Red Hat Enterprise Linux v8.9 or Amazon Linux 2

Note

If you are using internal storage, your volumes must be formatted as xfs.

In this system configuration, SQreamDB can store about 100TB of raw data (assuming an average compression ratio and ~30TB of usable raw storage).

If a NAS is used, the 10x SSD drives can be omitted, but SQreamDB recommends 2TB of local spool space on SSD or NVMe drives.

Multi-Node Cluster

Multi-node clusters can handle any number of concurrent users. A typical SQreamDB cluster relies on a minimum of two GPU-enabled servers and shared storage connected over a network fabric, such as InfiniBand EDR, 40GbE, or 100GbE.

The Multi-Node Cluster Examples section describes the following specifications:

The following table shows SQreamDB’s recommended hardware specifications:

Component

Type

Server

Dell R750, Dell R940xa, HP ProLiant DL380 Gen10 or similar (Intel only)

Processors

2x Intel Xeon Gold 6348 (28C/56HT) 3.5GHz or similar

RAM

2 TB

Onboard storage

  • 2x 960GB SSD 2.5in hot plug for OS, RAID1

  • 2x 2TB SSD or NVMe, for temporary spooling, RAID0

Network Card (Storage)

2x Mellanox ConnectX-6 Single Port HDR VPI InfiniBand Adapter cards at 100GbE or similar.

Network Card (Client)

2x 1 GbE cards or similar

External Storage

  • Mellanox Connectx5/6 100G NVIDIA Network Card (if applicable) or other high-speed network card minimum 40G compatible with customer’s infrastructure

  • 50 TB (NAS connected over GPFS, Lustre, Weka, or VAST) GPFS recommended

GPU

NVIDIA 2x A100, H100, or L40S

Operating System

Red Hat Enterprise Linux v8.9 or Amazon Linux 2

Metadata Server

The following table shows SQreamDB’s recommended metadata server specifications:

Component

Type

Server

Dell R750, Dell R940xa, HP ProLiant DL380 Gen10 or similar (Intel only)

Processors

2x Intel Xeon Gold 6342 2.8 Ghz 24C processors or similar

RAM

512GB DDR4 RAM 8x64GB RDIMM or similar

Onboard storage

2x 960 GB MVMe SSD drives in RAID 1 or similar

Network Card (Storage)

2x Mellanox ConnectX-6 Single Port HDR VPI InfiniBand Adapter cards at 100GbE or similar.

Network Card (Client)

2x 1 GbE cards or similar

Operating System

Red Hat Enterprise Linux v8.9 or Amazon Linux 2

Note

With a NAS connected over GPFS, Lustre, Weka, or VAST, each SQreamDB worker can read data at 5GB/s or more.

SQreamDB Studio Server

The following table shows SQreamDB’s recommended Studio server specifications:

Component

Type

Server

Physical or virtual machine

Processor

1x Intel Core i7

RAM

16 GB

Onboard storage

50 GB SSD 2.5in Hot-plug for OS, RAID1

Operating System

Red Hat Enterprise Linux v8.9

Cluster Design Considerations

This section describes the following cluster design considerations:

  • In a SQreamDB installation, the storage and computing are logically separated. While they may reside on the same machine in a standalone installation, they may also reside on different hosts, providing additional flexibility and scalability.

  • SQreamDB uses all resources in a machine, including CPU, RAM, and GPU to deliver the best performance. At least 256GB of RAM per physical GPU is recommended.

  • Local disk space is required for good temporary spooling performance, particularly when performing intensive operations exceeding the available RAM, such as sorting. SQreamDB recommends an SSD or NVMe drive in RAID0 configuration with about twice the RAM size available for temporary storage. This can be shared with the operating system drive if necessary.

  • When using NAS devices, SQreamDB recommends approximately 5GB/s of burst throughput from storage per GPU.

Balancing Cost and Performance

Prior to designing and deploying a SQreamDB cluster, a number of important factors must be considered.

The Balancing Cost and Performance section provides a breakdown of deployment details to ensure that this installation exceeds or meets the stated requirements. The rationale provided includes the necessary information for modifying configurations to suit the customer use-case scenario, as shown in the following table:

Component

Value

Compute - CPU

Balance price and performance

Compute – GPU

Balance price with performance and concurrency

Memory – GPU RAM

Balance price with concurrency and performance.

Memory - RAM

Balance price and performance

Operating System

Availability, reliability, and familiarity

Storage

Balance price with capacity and performance

Network

Balance price and performance

CPU Compute

SQreamDB relies on multi-core Intel Gold Xeon processors or IBM POWER9 processors and recommends a dual-socket machine populated with CPUs with 18C/36HT or better. While a higher core count may not necessarily affect query performance, more cores will enable higher concurrency and better load performance.

GPU Compute and RAM

The NVIDIA Tesla range of high-throughput GPU accelerators provides the best performance for enterprise environments. Most cards have ECC memory, which is crucial for delivering correct results every time. SQreamDB recommends the NVIDIA Tesla A100 80GB GPU for the best performance and highest concurrent user support.

GPU RAM, sometimes called GRAM or VRAM, is used for processing queries. It is possible to select GPUs with less RAM. However, the smaller GPU RAM results in reduced concurrency, as the GPU RAM is used extensively in operations like JOINs, ORDER BY, GROUP BY, and all SQL transforms.

RAM

SQreamDB requires using Error-Correcting Code memory (ECC), standard on most enterprise servers. Large amounts of memory are required for improved performance for heavy external operations, such as sorting and joining.

SQreamDB recommends at least 256GB of RAM per GPU on your machine.

Operating System

SQreamDB can run on the following 64-bit Linux operating systems:

  • Red Hat Enterprise Linux v8.9

  • Amazon Linux 2

Storage

For clustered scale-out installations, SQreamDB relies on NAS storage. For stand-alone installations, SQreamDB relies on redundant disk configurations, such as RAID 5, 6, or 10. These RAID configurations replicate blocks of data between disks to avoid data loss or system unavailability.

SQreamDB recommends using enterprise-grade SAS SSD or NVMe drives. For a 32-user configuration, the number of GPUs should roughly match the number of users. SQreamDB recommends 1 Tesla A100 / H100 or L40S GPU per 2 users, for full, uninterrupted dedicated access.