Azure AI Search vs. MongoDB

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Azure Cognitive Search
Score 7.9 out of 10
N/A
Azure AI Search (formerly Azure Cognitive Search) is enterprise search as a service, from Microsoft.
$0.10
Per Hour
MongoDB
Score 8.4 out of 10
N/A
MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
$0.10
million reads
Pricing
Azure AI SearchMongoDB
Editions & Modules
Basic
$0.101
Per Hour
Standard S1
$0.336
Per Hour
Standard S2
$1.344
Per Hour
Standard S3
$2.688
Per Hour
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
Offerings
Pricing Offerings
Azure Cognitive SearchMongoDB
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsFully managed, global cloud database on AWS, Azure, and GCP
More Pricing Information
Features
Azure AI SearchMongoDB
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Azure AI Search
-
Ratings
MongoDB
10.0
39 Ratings
12% above category average
Performance00 Ratings10.039 Ratings
Availability00 Ratings10.039 Ratings
Concurrency00 Ratings9.939 Ratings
Security00 Ratings9.939 Ratings
Scalability00 Ratings10.039 Ratings
Data model flexibility00 Ratings10.039 Ratings
Deployment model flexibility00 Ratings10.038 Ratings
Best Alternatives
Azure AI SearchMongoDB
Small Businesses
Yext
Yext
Score 8.9 out of 10
IBM Cloudant
IBM Cloudant
Score 7.7 out of 10
Medium-sized Companies
Guru
Guru
Score 9.3 out of 10
IBM Cloudant
IBM Cloudant
Score 7.7 out of 10
Enterprises
Guru
Guru
Score 9.3 out of 10
IBM Cloudant
IBM Cloudant
Score 7.7 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Azure AI SearchMongoDB
Likelihood to Recommend
7.0
(3 ratings)
10.0
(79 ratings)
Likelihood to Renew
-
(0 ratings)
10.0
(67 ratings)
Usability
-
(0 ratings)
10.0
(15 ratings)
Availability
-
(0 ratings)
9.0
(1 ratings)
Support Rating
-
(0 ratings)
9.6
(13 ratings)
Implementation Rating
-
(0 ratings)
8.4
(2 ratings)
User Testimonials
Azure AI SearchMongoDB
Likelihood to Recommend
Microsoft
Incredibly robust software for an enterprise organization to plug into their application. If you have a full development resource team at your disposal, this is great software and I highly recommend it. Largely, however, you won't be able to use this prior to the enterprise level. It's just too complicated and cumbersome of a product.
Read full review
MongoDB
If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
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Pros
Microsoft
  • Azure Search provides a fully-managed service for loading, indexing, and querying content.
  • Azure Search has an easy C# SDK that allows you to implement loading and retrieving data from the service very easy. Any developer with some Microsoft experience should feel immediate familiarity.
  • Azure Search has a robust set of abilities around slicing and presenting the data during a search, such as narrowing by geospatial data and providing an auto-complete capabilities via "Suggesters".
  • Azure Search has one-of-a-kind "Cognitive Search" capabilities that enable running AI algorithms over data to enrich it before it is stored into the service. For example, one could automatically do a sentiment analysis when ingesting the data and store that as one of the searchable fields on the content.
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MongoDB
  • Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
  • You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
  • Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
Read full review
Cons
Microsoft
  • Cross platform compatibility to integrate with various OS
  • Optimizing latency.
  • Nothing better than work on price, create more flexible options.
Read full review
MongoDB
  • An aggregate pipeline can be a bit overwhelming as a newcomer.
  • There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
  • Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
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Likelihood to Renew
Microsoft
No answers on this topic
MongoDB
I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
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Usability
Microsoft
No answers on this topic
MongoDB
NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
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Support Rating
Microsoft
No answers on this topic
MongoDB
Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
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Implementation Rating
Microsoft
No answers on this topic
MongoDB
While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
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Alternatives Considered
Microsoft
Azure Search is a competitor against Google's own AI autosuggest a feature. We went with Azure because our network security folks found it to be more robust from a security standpoint, which is incredibly important when you have proprietary manufacturing information. Additionally, we're a Microsoft shop so it plugged into our cloud hosting package and client facing OS.
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MongoDB
We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.
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Return on Investment
Microsoft
  • Azure Search enabled us to stand up a robust search capability with very few developer hours.
  • The fully-managed service of Azure Search means we get low cost of management (EG, DevOps) going into the future, even though the cost of the service itself definitely reflects the time saved.
  • Azure Search counts as a "Cognitive Service" for Microsoft Azure consumption and aligns our products with Microsoft's interests of driving an AI-first approach in the enterprise. Microsoft Partners, service and product companies alike, should be looking to align with this AI vision as it means favorable treatment from the Microsoft sales teams.
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MongoDB
  • Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
  • You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB
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ScreenShots

MongoDB Screenshots

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