Data Warehouse Flavors
DWS provides storage-compute coupled and decoupled data warehouses. For details about the differences between them, see Data Warehouse Types.
You are advised not to use clusters with low specifications, such as clusters with 16 GB memory and 4 vCPUs, in the production environment. Otherwise, resource overload may occur.
Flavors for Storage-Compute Coupled Clusters
- A storage-compute coupled data warehouse using cloud disks with a vCPU to memory ratio of 1:8 can be elastically scaled, providing unlimited computing and storage capacity. For details, see Table 1.
- A storage-compute coupled data warehouse using cloud disks with a vCPU to memory ratio of 1:4 provides high-concurrency, high-performance, and low-latency transaction processing capabilities at low costs based on large-scale data query and analysis capabilities. It is suitable for HTAP hybrid load scenarios and real-time analysis scenarios such as IoT. For details about flavors, see Table 2.
- A storage-compute coupled data warehouse using local disks cannot be scaled up. You can only increase capacity by adding more nodes. For details, see Table 3.
Step indicates the interval for increasing or decreasing the disk size during cluster configuration change. You need to select a value based on the storage step of the corresponding flavor.
| Flavor | CPU Architecture | vCPU | Memory (GB) | Storage Capacity Per Node | Default Storage | Step (GB) | Bandwidth | Recommended Storage (GB) | Number of DNs | Scenario |
|---|---|---|---|---|---|---|---|---|---|---|
| dwsx2.xlarge.m7 | x86 | 4 | 32 | 20 GB–2,000 GB | 100 | 10 | 1.5 Gbps | 800 | 1 | Suitable for DWS starters. These flavors can be used for testing, learning environments, or small-scale analytics systems. |
| dwsk2.xlarge | Arm | 4 | 32 | 20 GB–2,000 GB | 100 | 10 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 800 | 1 | |
| dwsx2.xlarge.m7n | x86 | 4 | 32 | 20 GB–2,000 GB | 100 | 10 | 2 Gbps | 800 | 1 | |
| dwsk2.xlarge.km2 | Arm | 4 | 32 | 20 GB–2,000 GB | 100 | 10 | 4 Gbps | 800 | 1 | |
| dwsx2.2xlarge.m7 | x86 | 8 | 64 | 100 GB–4,000 GB | 200 | 100 | 2 Gbps | 1,600 | 1 | Suitable for internal data warehousing and report analysis in small- and medium-sized enterprises (SMEs) |
| dwsk2.2xlarge | Arm | 8 | 64 | 100 GB–4,000 GB | 200 | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 1,600 | 1 | |
| dwsx2.2xlarge.m7n | x86 | 8 | 64 | 100 GB–4,000 GB | 200 | 100 | 3 Gbps | 1,600 | 1 | |
| dwsk2.2xlarge.km2 | Arm | 8 | 64 | 100 GB–4,000 GB | 200 | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 1,600 | 1 | |
| dwsx2.4xlarge.m7 | x86 | 16 | 128 | 100 GB–8,000 GB | 400 | 100 | 4 Gbps | 3,200 | 1 | |
| dwsk2.4xlarge | Arm | 16 | 128 | 100 GB–8,000 GB | 400 | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 3,200 | 1 | |
| dwsk2.4xlarge.km2 | Arm | 16 | 128 | 100 GB–8,000 GB | 400 | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 3,200 | 1 | |
| dwsx2.8xlarge.m7 | x86 | 32 | 256 | 100 GB–16,000 GB | 800 | 100 | 6 Gbps | 6,400 | 2 | Recommended for the production environment. These flavors are applicable to OLAP systems that have to deal with large data volumes, BI reports, and data visualizations on large screens for most companies. |
| dwsk2.8xlarge | Arm | 32 | 256 | 100 GB–16,000 GB | 800 | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 6,400 | 2 | |
| dwsx2.8xlarge.m7n | x86 | 32 | 256 | 100 GB–16,000 GB | 800 | 100 | 8 Gbps | 6,400 | 2 | |
| dwsk2.8xlarge.km2 | Arm | 32 | 256 | 100 GB–16,000 GB | 800 | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 6,400 | 2 | |
| dwsk2.12xlarge | Arm | 48 | 384 | 100 GB–24,000 GB | 1200 | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 9,600 | 4 | These flavors can deliver excellent performance and are applicable to high-throughput data warehouse processing and high-concurrency online query. |
| dwsx2.16xlarge.m7 | x86 | 64 | 512 | 100 GB–32,000 GB | 1,600 | 100 | 12 Gbps | 12,800 | 4 | |
| dwsx2.16xlarge.m7n | x86 | 64 | 512 | 100 GB–32,000 GB | 1,600 | 100 | 16 Gbps | 12,800 | 4 | |
| dwsk2.16xlarge | Arm | 64 | 512 | 100 GB–32,000 GB | 1,600 | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 12,800 | 4 | |
| dwsx2.24xlarge.m7 | x86 | 96 | 768 | 100 GB–48,000 GB | 2,400 | 100 | 16 Gbps | 19,200 | 4 | |
| dwsk2.24xlarge | Arm | 96 | 768 | 100 GB–48,000 GB | 2,400 | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 19,200 | 4 | |
| dwsx2.32xlarge.m7 | x86 | 128 | 1,024 | 100 GB–48,000 GB | 3,200 | 100 | 24 Gbps | 25,600 | 4 |
| Flavor | CPU Architecture | vCPUs | Memory (GB) | Storage Capacity Per Node | Step (GB) | Bandwidth | Number of DNs | Scenario |
|---|---|---|---|---|---|---|---|---|
| dwsx2.h.xlarge.4.c7 | x86 | 4 | 16 | 20 GB–2,000 GB | 20 | 1.5 Gbps | 1 | Suitable for DWS starters. These flavors can be used for testing, learning environments, or small-scale analytics systems. |
| dwsk2.h.xlarge.4.kc1 | Arm | 4 | 16 | 20 GB–2,000 GB | 20 | 1 Gbps | 1 | |
| dwsk2.h.xlarge.kc2 | Arm | 4 | 16 | 20 GB–2,000 GB | 20 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 1 | |
| dwsx2.h.xlarge.4.c7n | x86 | 4 | 16 | 20 GB–2,000 GB | 20 | 2 Gbps | 1 | |
| dwsx2.h.2xlarge.4.c6 | x86 | 8 | 32 | 100 GB–4,000 GB | 100 | 2 Gbps | 1 | Suitable for internal data warehousing and report analysis in small- and medium-sized enterprises (SMEs) |
| dwsx2.h.2xlarge.4.c7 | x86 | 8 | 32 | 100 GB–4,000 GB | 100 | 2 Gbps | 1 | |
| dwsk2.h.2xlarge.4.kc1 | Arm | 8 | 32 | 100 GB–4,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 1 | |
| dwsk2.h.2xlarge.kc2 | Arm | 8 | 32 | 100 GB–4,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 1 | |
| dwsx2.h.2xlarge.4.c7n | x86 | 8 | 32 | 100 GB–4,000 GB | 100 | 3 Gbps | 1 | |
| dwsx2.h.4xlarge.4.c7 | x86 | 16 | 64 | 100 GB–8,000 GB | 100 | 4 Gbps | 1 | Recommended for the production environment. These flavors are applicable to OLAP systems that have to deal with large data volumes, BI reports, and data visualizations on large screens for most companies. |
| dwsk2.h.4xlarge.4.kc1 | Arm | 16 | 64 | 100 GB–8,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 1 | |
| dwsk2.h.4xlarge.kc2 | Arm | 16 | 64 | 100 GB–8,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 1 | |
| dwsx2.h.4xlarge.4.c7n | x86 | 16 | 64 | 100 GB–8,000 GB | 100 | 4 Gbps | 1 | |
| dwsx2.h.8xlarge.4.c7 | x86 | 32 | 128 | 100 GB–16,000 GB | 100 | 7.5 Gbps | 2 | |
| dwsk2.h.8xlarge.4.kc1 | Arm | 32 | 128 | 100 GB–16,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 2 | |
| dwsk2.h.8xlarge.kc2 | Arm | 32 | 128 | 100 GB–16,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 2 | |
| dwsx2.h.8xlarge.4.c7n | x86 | 32 | 128 | 100 GB–16,000 GB | 100 | 8 Gbps | 2 | |
| dwsk2.h.12xlarge.4.kc1 | Arm | 48 | 192 | 100 GB–24,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 4 | These flavors can deliver excellent performance and are applicable to high-throughput data warehouse processing and high-concurrency online query. |
| dwsk2.h.12xlarge.kc2 | Arm | 48 | 192 | 100 GB–24,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 4 | |
| dwsx2.h.16xlarge.4.c7 | x86 | 64 | 256 | 100 GB–32,000 GB | 100 | 12 Gbps | 4 | |
| dwsx2.h.16xlarge.4.c7n | x86 | 64 | 256 | 100 GB–32,000 GB | 100 | 16 Gbps | 4 | |
| dwsk2.h.16xlarge | Arm | 64 | 256 | 100 GB–32,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 4 | |
| dwsk2.h.24xlarge | Arm | 96 | 384 | 100 GB–48,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 4 | |
| dwsk2.h.32xlarge | Arm | 128 | 512 | 100 GB–64,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 4 |
| Flavor | CPU Architecture | vCPUs | Memory (GB) | Bandwidth | Storage Capacity Per Node | Number of DNs | Scenario |
|---|---|---|---|---|---|---|---|
| dws2.olap.4xlarge.i3 | x86 | 16 | 128 | Single disk: Read throughput: 2.9 GiB/s Write throughput: 1.9 GiB/s | 1,490 GB | 1 | Recommended for the production environment. These flavors are applicable to OLAP systems that have to deal with large data volumes, BI reports, and data visualizations on large screens for most companies. These flavors can deliver excellent performance and are applicable to high-throughput data warehouse processing and high-concurrency online query. |
| dws2.olap.4xlarge.ki1 | Arm | 16 | 64 | Single disk: Read throughput: 2.9 GiB/s Write throughput: 1.9 GiB/s | 2,980 GB | 1 | |
| dws2.olap.8xlarge.i3 | x86 | 32 | 256 | Single disk: Read throughput: 2.9 GiB/s Write throughput: 1.9 GiB/s | 2,980 GB | 2 | |
| dws2.olap.8xlarge.ki1 | Arm | 32 | 128 | Single disk: Read throughput: 2.9 GiB/s Write throughput: 1.9 GiB/s | 5,960 GB | 2 | |
| dws2.olap.16xlarge.i3 | x86 | 64 | 512 | Single disk: Read throughput: 2.9 GiB/s Write throughput: 1.9 GiB/s | 5,960 GB | 4 | |
| dws2.olap.16xlarge.ki1 | Arm | 64 | 228 | Single disk: Read throughput: 2.9 GiB/s Write throughput: 1.9 GiB/s | 11,921 GB | 4 |
Flavors for Storage-Compute Decoupled Clusters
- A storage-compute decoupled data warehouse using cloud disks can be elastically scaled, providing unlimited computing and storage capacity. For details, see Table 4.
- A storage-compute decoupled data warehouse using local disks has a fixed storage capacity that cannot be expanded or modified. You can only increase capacity by adding more nodes. For details, see Table 5.
When creating a storage-compute decoupled cluster, only the second half of the flavors (for example, 4U16G.4DPU) are shown. The prefixes (dwsx3/dwsax3/dwsk3) in the flavor list indicate the storage-compute decoupled CPU architecture.
| Flavor | CPU Architecture | vCPUs | Memory (GB) | Storage Capacity Per Node | Step (GB) | Bandwidth | Number of DNs | Scenario |
|---|---|---|---|---|---|---|---|---|
| dwsx3.4U16G.4DPU | x86 | 4 | 16 | 20 GB–2,000 GB | 10 | 1.5 Gbps | 1 | Suitable for DWS starters. These flavors can be used for testing, learning environments, or small-scale analytics systems. |
| dwsk3.4U16G.4DPU | Arm | 4 | 16 | 20 GB–2,000 GB | 10 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 1 | |
| dwsax3.4U16G.4DPU | x86 | 4 | 16 | 20 GB–2,000 GB | 10 | 0.5 Gbps | 1 | |
| dwsax3.4U32G.4DPU | x86 | 4 | 32 | 20 GB–2,000 GB | 10 | 1.5 Gbps | 1 | |
| dwsx3.8U32G.8DPU | x86 | 8 | 32 | 100 GB–4,000 GB | 100 | 2 Gbps | 1 | Suitable for internal data warehousing and report analysis in small- and medium-sized enterprises (SMEs) |
| dwsk3.8U32G.8DPU | Arm | 8 | 32 | 100 GB–4,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 1 | |
| dwsax3.8U32G.8DPU | x86 | 8 | 32 | 100 GB–4,000 GB | 100 | 1.1 Gbps | 1 | |
| dwsax3.8U64G.8DPU | x86 | 8 | 64 | 100 GB–4,000 GB | 100 | 1 Gbps | 1 | |
| dwsx3.16U64G.16DPU | x86 | 16 | 64 | 100 GB–8,000 GB | 100 | 4 Gbps | 1 | Recommended for the production environment. These flavors are applicable to OLAP systems that have to deal with large data volumes, BI reports, and data visualizations on large screens for most companies. |
| dwsk3.16U64G.16DPU | Arm | 16 | 64 | 100 GB–8,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 1 | |
| dwsax3.16U64G.16DPU | x86 | 16 | 64 | 100 GB–8,000 GB | 100 | 2.1 Gbps | 1 | |
| dwsax3.16U128G.16DPU | x86 | 16 | 128 | 100 GB–8,000 GB | 100 | 2 Gbps | 1 | |
| dwsx3.32U128G.32DPU | x86 | 32 | 128 | 100 GB–16,000 GB | 100 | 6 Gbps | 2 | |
| dwsk3.32U128G.32DPU | Arm | 32 | 128 | 100 GB–16,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 2 | |
| dwsax3.32U128G.32DPU | x86 | 32 | 128 | 100 GB–16,000 GB | 100 | 4.3 Gbps | 2 | |
| dwsax3.32U256G.32DPU | x86 | 32 | 256 | 100 GB–16,000 GB | 100 | 4 Gbps | 2 | |
| dwsk3.48U192G.48DPU | Arm | 48 | 192 | 200 GB–24,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 4 | These flavors can deliver excellent performance and are applicable to high-throughput data warehouse processing and high-concurrency online query. |
| dwsx3.64U256G.64DPU | x86 | 64 | 256 | 200 GB–32,000 GB | 100 | 12 Gbps | 4 | |
| dwsk3.64U256G.64DPU | Arm | 64 | 256 | 100 GB–32,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 4 | |
| dwsax3.64U256G.64DPU | x86 | 64 | 256 | 100 GB–32,000 GB | 100 | 8.5 Gbps | 4 | |
| dwsax3.64U512G.64DPU | x86 | 64 | 512 | 100 GB–32,000 GB | 100 | 8 Gbps | 4 | |
| dwsx3.96U768G.96DPU | x86 | 96 | 768 | 100 GB–48,000 GB | 100 | 24 Gbps | 4 | |
| dwsk3.96U384G.96DPU | Arm | 96 | 384 | 100 GB–48,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 4 | |
| dwsax3.96U384G.96DPU | x86 | 96 | 384 | 100 GB–48,000 GB | 100 | 13 Gbps | 4 | |
| dwsax3.96U768G.96DPU | x86 | 96 | 768 | 100 GB–48,000 GB | 100 | 12 Gbps | 4 | |
| dwsx3.128U1024G.128DPU | x86 | 128 | 1,024 | 100 GB–64,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 4 | |
| dwsk3.128U512G.128DPU | Arm | 128 | 512 | 100 GB–64,000 GB | 100 | min (350, 120 + 0.5 × Capacity) MiB/s (capacity unit: GiB) | 4 | |
| dwsax3.128U512G.128DPU | x86 | 128 | 512 | 100 GB–64,000 GB | 100 | 17 Gbps | 4 | |
| dwsax3.128U1024G.128DPU | x86 | 128 | 1,024 | 100 GB–64,000 GB | 100 | 16 Gbps | 4 |
| Flavor | CPU Architecture | vCPUs | Memory (GB) | Bandwidth | Storage Capacity Per Node | Number of DNs | Scenario |
|---|---|---|---|---|---|---|---|
| dws3.16U128G.i7.16DPU | x86 | 16 | 128 | Single disk: Read throughput: 6.2 GiB/s Write throughput: 2.1 GiB/s | 2,980 GB | 1 | Recommended for the production environment. These flavors are applicable to OLAP systems that have to deal with large data volumes, BI reports, and data visualizations on large screens for most companies. These flavors can deliver excellent performance and are applicable to high-throughput data warehouse processing and high-concurrency online query. |
| dws3.16U64G.ki1.16DPU | Arm | 16 | 64 | Single disk: Read throughput: 2.9 GiB/s Write throughput: 1.9 GiB/s | 5,960 GB | 1 | |
| dws3.32U256G.i7.32DPU | x86 | 32 | 256 | Single disk: Read throughput: 6.2 GiB/s Write throughput: 2.1 GiB/s | 5,960 GB | 2 | |
| dws3.32U128G.ki1.32DPU | Arm | 32 | 128 | Single disk: Read throughput: 2.9 GiB/s Write throughput: 1.9 GiB/s | 11,920 GB | 2 | |
| dws3.64U512G.i7.64DPU | x86 | 64 | 512 | Single disk: Read throughput: 6.2 GiB/s Write throughput: 2.1 GiB/s | 11,920 GB | 4 | |
| dws3.64U228G.ki1.64DPU | Arm | 64 | 228 | Single disk: Read throughput: 2.9 GiB/s Write throughput: 1.9 GiB/s | 23,840 GB | 4 |
