Exam AZ-305 topic 2 question 18 discussion

Azure Synapse Analytics SQL pool only support 128 concurrent queries: "A maximum of 128 concurrent queries will execute and remaining queries will be queued" https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-service-capacity-limits Azure Sql hyperscale have read replica... and supports up to 100TB data size. So I think the correct answer should be Hyperscale

1. Data store for the ingestion data: b. Azure Data Lake Storage Gen2. Azure Data Lake Storage Gen2 is designed for big data analytics, it combines the power of a high-performance file system with massive scale and economy to help you speed up your big data analytics. It allows the data to be organized in directories by date and time. 2. Data store for the data warehouse: c. Azure SQL Database Hyperscale. Azure SQL Database Hyperscale is a highly scalable service tier that is designed to provide high performance, and supports up to 100 TB of data. The Hyperscale service tier in Azure SQL Database is the newest service tier in the vCore-based purchasing model. This service tier is a highly scalable storage and compute performance tier that leverages the Azure architecture to scale out the storage and compute resources for an Azure SQL Database substantially beyond the limits available for the General Purpose and Business Critical service tiers.

CORRECT

Data store for the ingested data: Azure Data Lake Storage Gen2 Data store for the data warehouse: Azure Synapse Analytics dedicated SQL pools

Data store for the ingested data: Azure Data Lake Storage Gen2: This service is optimized for big data analytics and can organize data by date and time. It also supports hierarchical namespace which is useful for efficient data organization. Data store for the data warehouse: Azure Synapse Analytics dedicated SQL pools: This service is designed to handle large-scale data warehousing, can store 50 TB of relational data, and supports high concurrency for read operations, making it suitable for your needs.

For the data store for ingested data, Azure Data Lake Storage Gen2 is recommended. It is designed to handle high volumes of data and allows you to organize data in directories by date and time. It also supports direct querying of stored data. For the data warehouse, Azure Synapse Analytics Dedicated SQL Pools is recommended. It is designed to handle large volumes of relational data (up to petabytes) and supports a high number of concurrent read operations. It also allows for data transformation into summarized tables. Azure Synapse Analytics integrates seamlessly with Azure Data Lake Storage Gen2, providing an end-to-end data solution.

Final Answer: 1. Azure Data Lake Storage Gen2. 2. Azure SQL Database Hyperscale.

Was on my Exam Today - 4th Jan 2024

For the ingested data, I recommend using zure Data Lake Storage Gen2. It is a highly scalable and cost-effective data lake solution for big data analytics. For the data warehouse, I recommend using Azure Synapse Analytics (formerly SQL Data Warehouse). It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless or provisioned resources at scale. It can store 50 TB of relational data and support between 200 and 300 concurrent read operations.

What would be right answer ?

If You dont know what to choose, choose cheapest one or "more cost safe" so IMO, Azure SQL Database Hyperscale is the answer even if Synapse meets requirements.

1. Data store for the ingested data: B. Azure Data Lake Storage Gen2 Azure Data Lake Storage Gen2 is designed for big data analytics workloads and supports organizing data in directories by date and time, as well as hierarchical namespace. It also allows stored data to be queried directly and is well-integrated with Azure Event Hubs. 2. Data store for the data warehouse: C. Azure SQL Database Hyperscale is an alternative option for the data store for the data warehouse. It is a highly scalable service tier for single databases within Azure SQL Database that can auto-scale up to 100 TB. It supports a large number of concurrent connections and offers rapid scaling capabilities.

The second is hyperscale: https://learn.microsoft.com/en-us/azure/azure-sql/database/service-tier-hyperscale-frequently-asked-questions-faq?view=azuresql#how-can-i-choose-between-azure-synapse-analytics-and-azure-sql-database-hyperscale- based on Microsoft docs. For this type of scenarios, Hyperscale works

Hyperscale is OLTP not OLAP (Data warehouse). Synapse is a DW

1. Azure Data Lake Storage Gen2 2. Azure SQL DB Hyperscale https://learn.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-introduction Azure Data Lake Storage Gen2 is a set of capabilities dedicated to big data analytics, built on Azure Blob Storage. Data Lake Storage Gen2 converges the capabilities of Azure Data Lake Storage Gen1 with Azure Blob Storage. For example, Data Lake Storage Gen2 provides file system semantics, file-level security, and scale. Because these capabilities are built on Blob storage, you'll also get low-cost, tiered storage, with high availability/disaster recovery capabilities. https://learn.microsoft.com/en-us/azure/azure-sql/database/service-tier-hyperscale?view=azuresql#what-are-the-hyperscale-capabilities The Hyperscale service tier in Azure SQL Database provides the following additional capabilities: - Support for up to 100 TB of database size.

I think the answer should be Azure Synapse Analytics SQLPool bcz: once data is stored in ADLS in directories, data needs to be queried directly and transformed and stored in tables. Synapse has that capability. ???

synapse vs hyperscale which is the better answer?