Azure Cognitive Search vs Azure Search: What are the differences?

Introduction

Azure Cognitive Search and Azure Search are both cloud-based search services offered by Microsoft. They enable developers to build powerful search solutions with features like full-text search, faceted navigation, and customizable ranking. While they share many similarities, there are key differences between the two services that sets them apart.

1. Data enrichment capabilities: Azure Cognitive Search offers advanced AI capabilities, allowing developers to extract insights from unstructured content using cognitive skills, which includes optical character recognition (OCR), entity recognition, and language detection. This enables better search relevance and more comprehensive search experiences. In contrast, Azure Search does not include these AI capabilities by default, making it more suitable for simpler search requirements without the need for data enrichment.

2. Cognitive Services integration: Azure Cognitive Search is tightly integrated with Azure Cognitive Services, a suite of AI and machine learning APIs. This integration enables developers to leverage the power of pre-trained models and APIs for tasks like image recognition, text analytics, and speech-to-text conversion within their search solutions. On the other hand, Azure Search does not provide this level of integration with Azure Cognitive Services.

3. Pricing model: Azure Cognitive Search has a different pricing model compared to Azure Search. With Azure Cognitive Search, you pay for the number of documents you index and the amount of data you store, along with the cognitive services utilized. In contrast, Azure Search has a pricing model based on the number of indexes and indexers you create, along with the amount of data stored. This distinction is important when choosing between the two services, depending on your specific requirements and budget.

4. Geo-replication capabilities: Azure Cognitive Search offers built-in geo-replication for higher availability and disaster recovery. This ensures that your search index and data are replicated across multiple Azure data centers, providing resilience and reducing the risk of data loss. In comparison, Azure Search does not natively provide this geo-replication feature, requiring additional configuration and management for achieving similar levels of availability.

5. Search scaling options: Azure Cognitive Search provides automatic scaling options to handle increased search query traffic. It can scale based on the query traffic and target response times, distributing the load across multiple replicas. In contrast, Azure Search requires manual scaling, where you need to provision and manage the number of search units based on your expected query loads. This difference in scaling options can impact the performance and cost-effectiveness of the search solution.

6. Availability of private endpoints: Azure Cognitive Search supports private endpoints, which allow you to securely access your search service over a private network connection or virtual network (VNet). This provides enhanced security by eliminating exposure to the public internet. Azure Search, however, does not have native support for private endpoints, making it more suitable for scenarios where internet access is permissible.

In summary, Azure Cognitive Search offers advanced AI capabilities, deep integration with Azure Cognitive Services, a different pricing model, built-in geo-replication, automatic search scaling, and support for private endpoints. On the other hand, Azure Search is a more lightweight option without AI capabilities, simpler pricing, and requires manual scaling.