Lakehouse Pricing
This page describes the pricing model and unit prices for Singdata Lakehouse, covering compute (measured in CRU*hour), storage, and network data transfer. AI Gateway model invocation is billed by tokens; for unit prices see AI Gateway Pricing. The pricing entry point is Pricing and Billing.
Overview of Billing Methods
Singdata Lakehouse is an integrated data platform built on cloud-native technology. The platform records the resources you consume in scenarios such as data integration, data analysis, storage, and network data transfer, and charges you accordingly based on three resource types — computing, storage, and network — depending on the cloud platform and region where the service occurs.
The billing of Singdata Lakehouse is mainly based on the following aspects:
- Computing Resources: The billing usage unit for computing resources is CRU*hour. The platform converts the computing power used and the actual runtime into CRU*hour usage. The use of general-purpose, analytical, and synchronous computing clusters for data integration or data analysis, IGS (Ingestion Service) for real-time data ingestion, tasks processed using Python or Shell scripts, and operations such as automatic materialized views (Auto_MV), data compression, and job scheduling automatically handled by the system will all generate computing resource consumption. Singdata will measure and bill based on the actual amount of computing power consumed.
- Storage Resources: The billing unit for storage resources is GiB, and billing is based on the actual storage capacity you use on Singdata Lakehouse. The following scenarios will occupy storage capacity: 1) Data stored in Lakehouse in the form of tables, materialized views, etc.; 2) Historical data retained after table updates or deletions; 3) Managed Table Volume and User Volume storage; 4) Cached query results.
- Network Data Transfer: The billing unit for network data transfer is GB, and billing is based on the actual amount of data transferred. The following scenarios will incur network data transfer fees: 1) Data queries through the public network, including full downloads of query results; 2) Data transfer between Singdata Lakehouse and other data sources; 3) Network connectivity through the Internet, cross-VPC connections, dedicated lines, or other methods. For Internet network traffic, only the data transfer volume flowing out of Singdata Lakehouse is measured; uploading data to Singdata Lakehouse is free of charge.
| Change Type | Affected Billing Items |
|---|---|
| Billing method change | Synchronous Computing Clusters (real-time and offline integration fees are consolidated under the "Synchronous Computing Cluster" billing item, and the CRU*hour unit price remains unchanged) |
| Newly charged items | IGS Service, Multi-Version Retained Storage, Managed table_volume, Managed user_volume, Result Cache, Network Data Transfer |
Billing Methods
Pay-as-you-go
In Singdata Lakehouse, all types of resources are flexibly scalable and used on-demand. You only need to pay for the amount of resources actually used.
| Resource Type | Metering Method | Settlement Cycle |
|---|---|---|
| Computing Resources | Metered by the second, with usage measured in CRU*hour | Every hour |
| Storage Resources | Sampled 24 hours a day, averaged | Every day |
| Network Data Transfer | Metered by actual traffic generated | Every hour |
This mode is primarily deducted through balance top-up via the Lakehouse console. Due to different prices of resources on different cloud platforms and in different regions, the unit prices of computing, storage, and network data transfer may vary. Please refer to the pricing tables below for prices; the actual bill within the system shall prevail. You can view resource usage and cost details on the "Management Center" - "Billing Statement" page.
Annual Prepaid
Singdata Lakehouse can also provide enterprise customers with specified resource specifications and annual prepaid billing methods. When using annual prepaid, the unit prices of computing and storage resources can offer corresponding discounts. For details, please contact Singdata sales personnel.
Billing Principles
Computing Resource Billing
The billing items for computing resources include six types: general-purpose computing clusters, analytical computing clusters, synchronous computing clusters, task scheduling, serverless jobs, and IGS Service. The billing cycle for computing resources is measured in hours.
The billing principles for each computing resource item are as follows:
General-purpose Computing Clusters
When a general-purpose computing cluster starts and reaches the "running" state, it begins to generate computing resource usage based on the cluster's specification size and number of instances. When the computing cluster enters the "stopping" state, it stops generating computing resource usage.
The minimum hourly usage for general-purpose computing resources is 1 CRU*hour, the maximum is 256 CRU*hour, with a step size of 1 CRU*hour. The table below shows the specifications and corresponding hourly computing resource usage:
| Cluster Specification | Hourly Computing Resource Usage (CRU*hour) |
|---|---|
| 1 | 1 |
| 2 | 2 |
| 3 | 3 |
| 4 | 4 |
| 5 | 5 |
| ... | ... |
| 256 | 256 |
Analytical Computing Clusters
The billing principle of analytical computing clusters is the same as that of general-purpose computing clusters, measured from the start time of the "running" state until entering the "stopping" state.
Analytical computing clusters support automatic instance scaling on top of the specifications. When query concurrency exceeds the maximum concurrency that all current instances can handle, the system will automatically scale out instances. Each additional instance increases the consumption of a computing cluster of the same specification. When reducing one instance still meets the current concurrency, the system will automatically scale in and reduce analytical computing resource consumption. Analytical clusters have elastic scaling enabled by default upon creation, with a default minimum of 1 instance and maximum of 2 instances. You can also manually set the minimum and maximum instance values for auto-scaling, with up to 25 instances.
The minimum hourly usage per instance for analytical computing resources is 1 CRU*hour, the maximum is 256 CRU*hour, with a step size of 2n CRU*hour. The table below shows the hourly computing resource usage for 1 to 5 instances:
| Cluster Specification | 1 Instance Hourly Consumption | 2 Instances Hourly Consumption | 3 Instances Hourly Consumption | 4 Instances Hourly Consumption | 5 Instances Hourly Consumption |
|---|---|---|---|---|---|
| 1 | 1 CRU*hour | 2 CRU*hour | 3 CRU*hour | 4 CRU*hour | 5 CRU*hour |
| 2 | 2 CRU*hour | 4 CRU*hour | 6 CRU*hour | 8 CRU*hour | 10 CRU*hour |
| 4 | 4 CRU*hour | 8 CRU*hour | 12 CRU*hour | 16 CRU*hour | 20 CRU*hour |
| 8 | 8 CRU*hour | 16 CRU*hour | 24 CRU*hour | 32 CRU*hour | 40 CRU*hour |
| 16 | 16 CRU*hour | 32 CRU*hour | 48 CRU*hour | 64 CRU*hour | 80 CRU*hour |
| 32 | 32 CRU*hour | 64 CRU*hour | 96 CRU*hour | 128 CRU*hour | 160 CRU*hour |
| 64 | 64 CRU*hour | 128 CRU*hour | 192 CRU*hour | 256 CRU*hour | 320 CRU*hour |
| 128 | 128 CRU*hour | 256 CRU*hour | 384 CRU*hour | 512 CRU*hour | 640 CRU*hour |
| 256 | 256 CRU*hour | 512 CRU*hour | 768 CRU*hour | 1024 CRU*hour | 1280 CRU*hour |
Synchronous Computing Clusters
Synchronous computing clusters are used for running data integration tasks, including offline integration and real-time integration. Multiple integration tasks can be submitted to the same synchronous computing cluster to reuse resources. Under the formal billing mode, the billing principle of synchronous computing clusters is the same as that of general-purpose computing clusters, measured from the start time of the "running" state until entering the "stopping" state.
Starting September 1, 2026, synchronous computing clusters will switch to the formal billing mode. Fees for real-time and offline integration will be recorded under the "Synchronous Computing Cluster" billing item.
Before September 1, 2026, synchronous computing clusters will continue to use the trial operation billing mode. The system records billing details separately under the "Offline Integration" and "Real-time Integration" billing items on a per-job basis according to actual resource consumption. The CRU*hour unit price remains unchanged under this billing model. When creating a synchronous cluster, you can use the "Specification Estimation" feature to help determine the appropriate size.
Offline integration tasks can automatically wake up the synchronous computing cluster and automatically stop it after the task is completed; real-time integration tasks require their synchronous computing cluster to remain in the "running" state.
The minimum hourly usage for a synchronous computing cluster is 0.05 CRU*hour, the maximum is 256 CRU*hour, and the step size is 0.025 CRU*hour. The hourly computing resource usage has the same numeric value as the configured cluster specification, for example:
| Cluster Specification | Hourly Computing Resource Usage (CRU*hour) |
|---|---|
| 0.05 | 0.05 CRU*hour |
| 0.075 | 0.075 CRU*hour |
| 0.1 | 0.1 CRU*hour |
| ... | ... |
| 256 | 256 CRU*hour |
Task Scheduling
Task scheduling billing mainly covers two types of scenarios: one is the scheduling computing resource consumption generated when Python, Shell, and other script tasks are executed; the other is the small amount of computing resource consumption generated during the job submission and scheduling management process of offline and real-time integration tasks.
Task scheduling has no fixed minimum specification or step size restrictions. In all scenarios, the actual resource consumption from task scheduling will generate billing in CRU*hour units.
For Python, Shell, and other script tasks, the system will meter based on the computing resources allocated to the task and the actual runtime. The metering period starts when the task execution begins and ends when the task execution completes.
For offline integration tasks, Singdata Lakehouse provides a small amount of computing resources for job submission and scheduling management. These resources begin metering after the offline integration task starts, do not consume during queue waiting, and persist throughout task execution.
For real-time integration tasks, Singdata Lakehouse similarly provides a small amount of computing resources for job submission and scheduling management. These resources begin metering after the real-time integration task starts and end after the task is officially running. Computing resource consumption during this period will be metered.
Serverless Jobs
Serverless jobs refer to jobs that do not require users to actively create computing cluster instances, but are handled by the public computing resources provided by Singdata Lakehouse. This includes query job scheduling, data compression, automatic materialized views, etc.
The current CRU*hour unit price for serverless jobs is the same as that of general-purpose computing clusters.
IGS Service
IGS (Ingestion Service) is ClickZetta Lakehouse's service for real-time data ingestion. Clients can push data to IGS through the RealtimeStream SDK or CDC. IGS receives the data and commits it to the target table, enabling real-time writes and relatively fast queries. It is suitable for scenarios such as real-time analytics, event stream processing, and immediate data updates.
IGS Service fees will be officially charged starting September 1, 2026.
Storage Capacity Billing
Storage fees are calculated based on the actual storage capacity you use on the Lakehouse platform. The billing cycle for storage is measured in days.
Table Storage
When you write data into the Lakehouse data warehouse, the written data and some of its metadata information will occupy storage capacity in Lakehouse. Lakehouse measures your actual data storage usage by sampling multiple times within a day and uses the average value of the sampled storage capacity as the storage capacity measurement value for that day for billing.
Multi-Version Retained Storage
After table data is updated or deleted, Lakehouse continues to retain the corresponding historical data versions for the duration of the retention period, forming multi-version retained storage. This storage provides the underlying storage for historical version features such as Time Travel; it is not a charge for Time Travel query operations themselves.
Multi-version retained storage fees will be officially charged starting September 1, 2026.
Managed table_volume Storage
Each table is automatically associated with a Table Volume storage space for import, export, and ETL files related to that table. The table_volume is managed by Lakehouse and exists with the table; it does not store the table's live data.
Managed table_volume storage fees will be officially charged starting September 1, 2026.
Managed user_volume Storage
Each user automatically has a dedicated User Volume storage space for uploading local files, temporarily storing data to be processed, or importing files into tables. The user_volume is managed by Lakehouse and cannot be accessed by other users.
Managed user_volume storage fees will be officially charged starting September 1, 2026.
Result Cache
When you perform SQL queries, the query results are cached to reduce the computing resources consumed by repeated queries, exchanging storage costs for computing resource savings. This storage usage is included in Result Cache.
Result Cache fees will be officially charged starting September 1, 2026.
Network Data Transfer Billing
Network data transfer is billed in GB; only downstream data flowing out of Lakehouse is charged, while upstream data transferred into Lakehouse is not charged; fees are calculated based on the actual downstream transfer volume, with a billing cycle measured in hours. The following scenarios incur network data transfer fees:
Data Integration Traffic
Traffic generated when data integration tasks write data to external data sources.
Query and Download Traffic
Traffic generated when query results are returned to the user side (such as SQLLine, Lakehouse Studio, etc.) or when data is downloaded or exported.
Fees from Network Connectivity
When you use dedicated lines, Private Link, or other network products to establish cross-cloud vendor, cross-region, or cross-VPC connectivity, the network connectivity itself also incurs additional data transfer fees. Because the link involves both the Singdata Lakehouse side and your cloud platform account side, these fees are charged separately by each party: the portion generated on the Singdata Lakehouse side is charged by Singdata, and the portion generated in your cloud platform account is charged directly by the cloud platform.
Network data transfer fees will be officially charged starting September 1, 2026.
Other Cloud Resource Billing
When Singdata Lakehouse performs metadata management, parses SQL statements, generates query plans, schedules and allocates query tasks, and merges and cleans data files, it will consume cloud resources. Lakehouse will meter the consumption of these cloud resources, which are currently free for a limited time. You will be notified one month in advance when the billing status changes.
Pricing
Computing Resource Price
Standard Edition:
| Cloud Provider | Region | Version | Unit Price |
|---|---|---|---|
| Alibaba Cloud | Singapore | Standard Edition | 0.8 USD/CRU*hour |
| AWS | Singapore | Standard Edition | 1.24 USD/CRU*hour |
Enterprise Edition:
| Cloud Provider | Region | Version | Unit Price |
|---|---|---|---|
| Alibaba Cloud | Singapore | Enterprise Edition | 1.2 USD/CRU*hour |
| AWS | Singapore | Enterprise Edition | 1.86 USD/CRU*hour |
Note: In addition to the Standard Edition, the platform also offers an Enterprise Edition with enhanced data governance and security capabilities. The CRU*hour unit price for the Enterprise Edition is higher than that of the Standard Edition. For a detailed comparison of features between the two editions, please refer to the product documentation at Editions Overview.
Storage Capacity Price
| Cloud Provider | Region | Version | Storage Capacity Price |
|---|---|---|---|
| Alibaba Cloud | Singapore | Enterprise Edition & Standard Edition | 0.017 USD/GiB/month |
| AWS | Singapore | Enterprise Edition & Standard Edition | 0.025 USD/GiB/month |
Note: Since the billing cycle for storage is measured in days, the monthly unit price shown above is prorated on a 30-day basis for daily deductions.
Network Data Transfer Pricing
Network data transfer fees will be officially charged starting September 1, 2026.
| Cloud Provider | Region | Edition | Network Data Transfer Price |
|---|---|---|---|
| Alibaba Cloud | Singapore | Enterprise Edition & Standard Edition | 0.08 USD/GB |
| AWS | Singapore | Enterprise Edition & Standard Edition | 0.12 USD/GB |
Cost Examples in Common Scenarios
General-purpose Computing Cluster Cost Example
Taking an AWS Singapore Enterprise Edition service instance in SaaS mode as an example:
-
A general-purpose computing cluster with hourly computing resource usage of 2 CRU*hour, running for 1 hour, with a unit price of 1.86 USD per CRU*hour, the cost is:
- 1 hour × 2 CRU*hour × 1.86 USD/CRU*hour = 3.72 USD
-
A general-purpose computing cluster with hourly computing resource usage of 1 CRU*hour, running for 1 minute and 20 seconds (approximately 1.33 minutes), with a unit price of 1.86 USD per CRU*hour, the cost is:
- 1.33/60 minutes × 1 CRU*hour × 1.86 USD/CRU*hour = 0.041 USD
-
A general-purpose computing cluster with hourly computing resource usage of 1 CRU*hour running from 10:00-10:02 for 2 minutes, and another general-purpose computing cluster with hourly computing resource usage of 2 CRU*hour running from 10:00-10:10 for 10 minutes, with a unit price of 1.86 USD per CRU*hour, the cost is:
- (2/60 minutes × 1 CRU*hour × 1.86 USD/CRU*hour) + (10/60 minutes × 2 CRU*hour × 1.86 USD/CRU*hour) = 0.062 USD + 0.620 USD = 0.682 USD
Analytical Computing Cluster Cost Example
Taking an AWS Singapore Enterprise Edition service instance in SaaS mode as an example:
- An analytical cluster with hourly computing resource usage of 1 CRU*hour per instance, running for 30 minutes with 1 instance, and then running for 30 minutes with 2 instances, with a unit price of 1.86 USD per CRU*hour, the cost is:
- (30/60 minutes × 1 instance × 1 CRU*hour × 1.86 USD/CRU*hour) + (30/60 minutes × 2 instances × 1 CRU*hour × 1.86 USD/CRU*hour) = 0.93 USD + 1.86 USD = 2.79 USD
Offline Integration Task Cost Example
The following examples apply only to the trial operation period before September 1, 2026. Offline integration tasks are not charged separately; only the running costs of the synchronous computing cluster to which the tasks are submitted are charged. Offline integration tasks can automatically wake up the synchronous computing cluster.
An offline integration task generates computing resource usage for scheduling and concurrent execution. A single offline task typically generates at least approximately 0.05 CRU*hour of scheduling resource usage per hour, with total hourly usage of at least approximately 0.1 CRU*hour (0.05 CRU*hour + 1 × 0.05 CRU*hour). Based on this estimate, 5 single-concurrent offline integration tasks can fully utilize a synchronous computing cluster with hourly computing resource usage of 0.5 CRU*hour.
Taking an AWS Singapore Enterprise Edition service instance in SaaS mode as an example:
-
A single-concurrent offline integration task running for 10 minutes, with hourly computing resource usage of 0.1 CRU*hour, and a unit price of 1.86 USD per CRU*hour, the cost is:
- 10/60 minutes × 0.1 CRU*hour × 1.86 USD/CRU*hour = 0.031 USD
-
A single-concurrent offline integration task running from 10:00-10:10 for 10 minutes with hourly computing resource usage of 0.1 CRU*hour, and another 5-concurrent offline integration task running from 10:05-10:25 for 20 minutes with hourly computing resource usage of 0.3 CRU*hour, with a unit price of 1.86 USD per CRU*hour, the cost is:
- (5/60 minutes × 0.1 CRU*hour × 1.86 USD/CRU*hour) + (5/60 minutes × 0.4 CRU*hour × 1.86 USD/CRU*hour) + (15/60 minutes × 0.3 CRU*hour × 1.86 USD/CRU*hour) = 0.016 USD + 0.062 USD + 0.140 USD = 0.217 USD
Real-time Integration Task Cost Example
The following examples apply only to the trial operation period before September 1, 2026. In addition to offline integration tasks, the computing resource consumption of real-time integration tasks in the synchronous computing cluster is also metered separately.
Unlike offline integration tasks, real-time integration tasks run continuously after startup and perform real-time data caching and state management in memory. Therefore, the execution resource usage of real-time tasks does not have a simple linear relationship with concurrency, but mainly depends on the complexity of data processing and the required state cache size. A single-concurrent real-time integration task generates at least approximately 0.05 CRU*hour of scheduling resource usage and approximately 0.0625 CRU*hour of execution resource usage per hour, totaling at least approximately 0.1125 CRU*hour.
Taking an AWS Singapore Enterprise Edition service instance in SaaS mode as an example:
- A single-concurrent real-time integration task running for 24 hours, with hourly computing resource usage of 0.1125 CRU*hour, and a unit price of 1.86 USD per CRU*hour, the cost is:
- 24 hours × 0.1125 CRU*hour × 1.86 USD/CRU*hour = 5.022 USD
- A multi-concurrent real-time integration task with hourly computing resource usage of 1 CRU*hour running from January 1-5 for 5 days, and another multi-concurrent real-time integration task with hourly computing resource usage of 2 CRU*hour running from January 3-10 for 8 days, with a unit price of 1.86 USD per CRU*hour, the cost is:
- (2 × 24 hours × 1 CRU*hour × 1.86 USD/CRU*hour) + (3 × 24 hours × 3 CRU*hour × 1.86 USD/CRU*hour) + (5 × 24 hours × 2 CRU*hour × 1.86 USD/CRU*hour) = 89.28 USD + 402.48 USD + 446.40 USD = 938.16 USD
Synchronous Computing Cluster Cost Example
Starting September 1, 2026, synchronous computing clusters will be billed according to this standard.
Taking an AWS Singapore Enterprise Edition service instance in SaaS mode as an example:
-
A synchronous cluster with hourly computing resource usage of 2 CRU*hour, running for 1 hour, with a unit price of 1.86 USD per CRU*hour, the cost is:
- 1 hour × 2 CRU*hour × 1.86 USD/CRU*hour = 3.72 USD
-
A real-time integration task with hourly computing resource usage of 0.2 CRU*hour running from January 1-5 for 5 days, with an additional offline integration task with hourly computing resource usage of 0.1 CRU*hour running for 1 hour on January 2 from 0:00-1:00, with a unit price of 1.86 USD per CRU*hour, the cost is:
- "Fixed" mode total cost: 5 × 24 hours × 0.5 CRU*hour × 1.86 USD/CRU*hour = 111.60 USD
- "Elastic Scaling" mode total cost: (1 × 24 hours × 0.25 CRU*hour × 1.86 USD/CRU*hour) + (1 hour × 0.5 CRU*hour × 1.86 USD/CRU*hour) + ((23 + 3×24) hours × 0.25 CRU*hour × 1.86 USD/CRU*hour) = 11.16 USD + 0.93 USD + 44.22 USD = 56.31 USD
As shown in the examples above, to better save synchronous computing resource costs, it is recommended to reuse synchronous computing cluster resources as much as possible and avoid using overly large specifications.
Task Scheduling - Python Script Task Cost Example
When executing Python script tasks, the cost is calculated based on the task execution time and the computing resource usage generated. Generally, a Python script generates 0.125 CRU*hour of computing resource usage per hour.
Taking an AWS Singapore Enterprise Edition service instance in SaaS mode as an example:
- A Python script task with an execution time of 10 minutes, with a unit price of 1.86 USD per CRU*hour, the cost is:
- 10/60 minutes × 0.125 CRU*hour × 1.86 USD/CRU*hour = 0.039 USD
Storage Capacity Cost Example
Taking an AWS Singapore Enterprise Edition service instance in SaaS mode as an example:
- A workspace with a daily storage capacity low point of 910 GiB, high point of 1100 GiB, and daily average of 1000 GiB, with a monthly storage unit price of 0.025 USD/GiB/month (calculated on a 30-day basis), the storage cost for that day is:
- 1/30 month × 1000 GiB × 0.025 USD/GiB/month = 0.833 USD
Network Data Transfer Cost Example
Taking an AWS Singapore Enterprise Edition service instance in SaaS mode as an example:
- A task generating 10 GB of outbound network data transfer, with a network data transfer unit price of 0.12 USD/GB, the network data transfer cost is:
- 10 GB × 0.12 USD/GB = 1.20 USD