Update analytical-store-introduction.md

Author: Rodrigossz

articles/cosmos-db/analytical-store-introduction.md

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 Azure Cosmos DB transactional store is schema-agnostic, and it allows you to iterate on your transactional applications without having to deal with schema or index management. In contrast to this, Azure Cosmos DB analytical store is schematized to optimize for analytical query performance. This article describes in detailed about analytical storage.
 
-> [!NOTE]
-> Synapse Link for Gremlin API is now in preview. You can enable Synapse Link in your new or existing graphs using Azure CLI. For more information on how to configure it, click [here](configure-synapse-link.md).
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 ## Challenges with large-scale analytics on operational data
 
 The multi-model operational data in an Azure Cosmos DB container is internally stored in an indexed row-based "transactional store". Row store format is designed to allow fast transactional reads and writes in the order-of-milliseconds response times, and operational queries. If your dataset grows large, complex analytical queries can be expensive in terms of provisioned throughput on the data stored in this format. High consumption of provisioned throughput in turn, impacts the performance of transactional workloads that are used by your real-time applications and services.