价钱 当您使用空间和时间时，您所付出的只是计算。存储、索引区块链数据、OpenAI 仪表板、集群中的 OLTP + OLAP 查询、SQL 加密证明等始终包含在内。

我们提供多种不同的定价选项来满足您的需求和用例。请访问我们的定价页面，详细了解哪种选项最适合您。

关于按计算付费 按计算付费是 Space and Time 的基于使用情况的定价选项，让您只需为运行的查询付费。计算成本是使用类似gas的模型来计算的，其中计算消耗以空间和时间积分来衡量。消耗的计算量取决于确切的查询、数据大小以及返回的数据量。

为了让您了解在按计算付费模型下不同查询的成本，我们提供了一组针对各种 public_read 表的查询及其经过测试的积分消耗。

目前，1 个计算积分的成本= 1 USD。

🚧 关于测试版的注意事项

请注意，按计算付费仍处于测试阶段，下面的估算可能会随着时间的推移而发生变化。您可以随时返回此页面查看最新的估算。

一般观察：大型表按字段进行分区，这意味着只要您对未修改的字段进行操作，时间限制查询将比无限制查询（也称为全表扫描）消耗更少的资源，如下面的示例所示。 Time_StampTime_Stamp

如果您需要对所有无限历史记录（即获取地址的完整历史记录）进行频繁查询，您可以考虑创建物化视图。

单行表查找 SQL

SELECT * FROM sxtlabs.singularity 挂钟时间 制作人员 93毫秒 0.000037125 多行查找 SQL

SELECT * FROM sxtdemo.stocks WHERE STOCK_DATE = '2023-11-21' 挂钟时间 制作人员 94毫秒 0.000621000 简单解析 SQL

SELECT SYMBOL, AVG((STOCK_HIGH-STOCK_LOW) / STOCK_OPEN) AS Avg_Volatility FROM sxtdemo.stocks WHERE SYMBOL in ('MSFT','AMZN','GOOGL') GROUP BY SYMBOL 挂钟时间 制作人员 748毫秒 0.008040050 简单分析，大扫描 SQL

SELECT cast(TIME_STAMP AS date) AS Create_Date, count(*) AS Contracts_Created FROM POLYGON.CONTRACTS WHERE TIME_STAMP BETWEEN '2023-01-01' AND '2023-04-30' -- 200k of 2M ROWS, 10% GROUP BY 1 ORDER BY 1 desc 挂钟时间 制作人员 5秒 0.222452000 中等分析 SQL

SELECT avg(Block_Count) AS DailyAvg_Block_Count ,avg(Validator_Reward_Matic) AS DailyAvg_Validator_Reward_Matic ,avg(Gas_Used_Matic) AS DailyAvg_Gas_Used_Matic ,round(avg(Avg_Txn_per_Block),2) AS DailyAvg_Txn_per_Block FROM ( SELECT cast(TIME_STAMP AS date) AS Block_Date ,sum(REWARD)/1e18 AS Validator_Reward_Matic ,sum(GAS_USED)/1e18 AS Gas_Used_Matic ,AVG(TRANSACTION_COUNT) AS Avg_Txn_per_Block ,count(*) AS Block_Count FROM POLYGON.BLOCKS WHERE TIME_STAMP BETWEEN '2023-01-01' AND '2023-01-26' -- 1M ROWS GROUP BY 1 ) AS a 挂钟时间 制作人员 2秒 0.058209900 大型分析 跨 3 个不同的链查询整个 EVENT.LOG 表（曾经触发的每个智能合约事件 - 任何模型中最大的单个表）。

SQL

SELECT p.Event_Date ,p.Event_Cnt AS Polygon_Event_Count ,p.Event_Cnt - lead(p.Event_Cnt) over(ORDER BY p.Event_Date desc) AS Polygon_Event_Growth ,round((1-(lead(p.Event_Cnt)over(ORDER BY p.Event_Date desc) / p.Event_Cnt))100,2)||'%' AS Polygon_Event_Growth_Pct ,e.Event_Cnt AS Ethereum_Event_Count ,e.Event_Cnt - lead(e.Event_Cnt) over(ORDER BY e.Event_Date desc) AS Ethereum_Event_Growth ,round((1-(lead(e.Event_Cnt)over(ORDER BY e.Event_Date desc) / e.Event_Cnt))100,2)||'%' AS Ethereum_Event_Growth_Pct ,s.Event_Cnt AS Sui_Event_Count ,s.Event_Cnt - lead(s.Event_Cnt) over(ORDER BY s.Event_Date desc) AS Sui_Event_Growth ,round((1-(lead(s.Event_Cnt)over(ORDER BY s.Event_Date desc) / s.Event_Cnt))100,2)||'%' AS Sui_Event_Growth_Pct FROM ( SELECT CAST(p1.TIME_STAMP AS date) AS Event_Date ,count() AS Event_Cnt FROM POLYGON.LOGS AS p1 WHERE p1.TIME_STAMP BETWEEN '2023-08-01' AND '2023-08-31T23:59:59' GROUP BY 1 ) AS p LEFT OUTER JOIN ( SELECT CAST(e1.TIME_STAMP AS date) AS Event_Date ,count() AS Event_Cnt FROM ETHEREUM.LOGS e1 WHERE e1.TIME_STAMP BETWEEN '2023-08-01' AND '2023-08-31T23:59:59' GROUP BY 1 ) AS e ON p.Event_Date = e.Event_Date LEFT OUTER JOIN ( SELECT CAST(s1.TIME_STAMP AS date) AS Event_Date ,count() AS Event_Cnt FROM SUI.EVENTS AS s1 WHERE s1.TIME_STAMP BETWEEN '2023-08-01' AND '2023-08-31T23:59:59' GROUP BY 1 ) AS s ON p.Event_Date = s.Event_Date 挂钟时间 制作人员 10秒 0.52894240

价钱 当您使用空间和时间时，您所付出的只是计算。存储、索引区块链数据、OpenAI 仪表板、集群中的 OLTP + OLAP 查询、SQL 加密证明等始终包含在内。

我们提供多种不同的定价选项来满足您的需求和用例。请访问我们的定价页面，详细了解哪种选项最适合您。

关于按计算付费 按计算付费是 Space and Time 的基于使用情况的定价选项，让您只需为运行的查询付费。计算成本是使用类似gas的模型来计算的，其中计算消耗以空间和时间积分来衡量。消耗的计算量取决于确切的查询、数据大小以及返回的数据量。

为了让您了解在按计算付费模型下不同查询的成本，我们提供了一组针对各种 public_read 表的查询及其经过测试的积分消耗。

目前，1 个计算积分的成本= 1 USD。

🚧 关于测试版的注意事项

请注意，按计算付费仍处于测试阶段，下面的估算可能会随着时间的推移而发生变化。您可以随时返回此页面查看最新的估算。

一般观察：大型表按字段进行分区，这意味着只要您对未修改的字段进行操作，时间限制查询将比无限制查询（也称为全表扫描）消耗更少的资源，如下面的示例所示。 Time_StampTime_Stamp

如果您需要对所有无限历史记录（即获取地址的完整历史记录）进行频繁查询，您可以考虑创建物化视图。

单行表查找 SQL

SELECT * FROM sxtlabs.singularity 挂钟时间 制作人员 93毫秒 0.000037125 多行查找 SQL

SELECT * FROM sxtdemo.stocks WHERE STOCK_DATE = '2023-11-21' 挂钟时间 制作人员 94毫秒 0.000621000 简单解析 SQL

SELECT SYMBOL, AVG((STOCK_HIGH-STOCK_LOW) / STOCK_OPEN) AS Avg_Volatility FROM sxtdemo.stocks WHERE SYMBOL in ('MSFT','AMZN','GOOGL') GROUP BY SYMBOL 挂钟时间 制作人员 748毫秒 0.008040050 简单分析，大扫描 SQL

SELECT cast(TIME_STAMP AS date) AS Create_Date, count(*) AS Contracts_Created FROM POLYGON.CONTRACTS WHERE TIME_STAMP BETWEEN '2023-01-01' AND '2023-04-30' -- 200k of 2M ROWS, 10% GROUP BY 1 ORDER BY 1 desc 挂钟时间 制作人员 5秒 0.222452000 中等分析 SQL

SELECT avg(Block_Count) AS DailyAvg_Block_Count ,avg(Validator_Reward_Matic) AS DailyAvg_Validator_Reward_Matic ,avg(Gas_Used_Matic) AS DailyAvg_Gas_Used_Matic ,round(avg(Avg_Txn_per_Block),2) AS DailyAvg_Txn_per_Block FROM ( SELECT cast(TIME_STAMP AS date) AS Block_Date ,sum(REWARD)/1e18 AS Validator_Reward_Matic ,sum(GAS_USED)/1e18 AS Gas_Used_Matic ,AVG(TRANSACTION_COUNT) AS Avg_Txn_per_Block ,count(*) AS Block_Count FROM POLYGON.BLOCKS WHERE TIME_STAMP BETWEEN '2023-01-01' AND '2023-01-26' -- 1M ROWS GROUP BY 1 ) AS a 挂钟时间 制作人员 2秒 0.058209900 大型分析 跨 3 个不同的链查询整个 EVENT.LOG 表（曾经触发的每个智能合约事件 - 任何模型中最大的单个表）。

SQL

SELECT p.Event_Date ,p.Event_Cnt AS Polygon_Event_Count ,p.Event_Cnt - lead(p.Event_Cnt) over(ORDER BY p.Event_Date desc) AS Polygon_Event_Growth ,round((1-(lead(p.Event_Cnt)over(ORDER BY p.Event_Date desc) / p.Event_Cnt))100,2)||'%' AS Polygon_Event_Growth_Pct ,e.Event_Cnt AS Ethereum_Event_Count ,e.Event_Cnt - lead(e.Event_Cnt) over(ORDER BY e.Event_Date desc) AS Ethereum_Event_Growth ,round((1-(lead(e.Event_Cnt)over(ORDER BY e.Event_Date desc) / e.Event_Cnt))100,2)||'%' AS Ethereum_Event_Growth_Pct ,s.Event_Cnt AS Sui_Event_Count ,s.Event_Cnt - lead(s.Event_Cnt) over(ORDER BY s.Event_Date desc) AS Sui_Event_Growth ,round((1-(lead(s.Event_Cnt)over(ORDER BY s.Event_Date desc) / s.Event_Cnt))100,2)||'%' AS Sui_Event_Growth_Pct FROM ( SELECT CAST(p1.TIME_STAMP AS date) AS Event_Date ,count() AS Event_Cnt FROM POLYGON.LOGS AS p1 WHERE p1.TIME_STAMP BETWEEN '2023-08-01' AND '2023-08-31T23:59:59' GROUP BY 1 ) AS p LEFT OUTER JOIN ( SELECT CAST(e1.TIME_STAMP AS date) AS Event_Date ,count() AS Event_Cnt FROM ETHEREUM.LOGS e1 WHERE e1.TIME_STAMP BETWEEN '2023-08-01' AND '2023-08-31T23:59:59' GROUP BY 1 ) AS e ON p.Event_Date = e.Event_Date LEFT OUTER JOIN ( SELECT CAST(s1.TIME_STAMP AS date) AS Event_Date ,count() AS Event_Cnt FROM SUI.EVENTS AS s1 WHERE s1.TIME_STAMP BETWEEN '2023-08-01' AND '2023-08-31T23:59:59' GROUP BY 1 ) AS s ON p.Event_Date = s.Event_Date 挂钟时间 制作人员 10秒 0.52894240