Google Cloud Bigtable vs Microsoft Azure Cosmos DB comparison

Google and Microsoft are both solutions in the Managed NoSQL Databases category. Google is ranked #7 with an average rating of 9.7, while Microsoft is ranked #1 with an average rating of 8.2. Google holds a 7.9% mindshare in MND, compared to Microsoft’s 17.8% mindshare. Additionally, 100% of Google users are willing to recommend the solution, compared to 95% of Microsoft users who would recommend it.

Google Cloud Bigtable

Read 6 Google Cloud Bigtable reviews

1,185 Views
674 Comparison Views

100% willing to recommend

Microsoft Azure Cosmos DB

Read 61 Microsoft Azure Cosmos DB reviews

3,593 Views
1,384 Comparison Views

95% willing to recommend

Google Cloud Bigtable

Microsoft Azure Cosmos DB

Comparison Buyer's Guide

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Executive SummaryUpdated on Sep 29, 2024

Google Cloud Bigtable and Microsoft Azure Cosmos DB are leading NoSQL database solutions, each excelling in different areas. Data comparisons show that while users find the pricing of Google Cloud Bigtable more favorable, Azure Cosmos DB's advanced features and global distribution capabilities make it worth the higher price.

Features: Users highlight Google Cloud Bigtable's robust scalability, real-time analytics, and high throughput as its most valuable features. In contrast, Azure Cosmos DB users value its multi-model support, global low-latency, and flexible schema options. Despite both products being feature-rich, Azure Cosmos DB's versatility gives it an edge.

Room for Improvement: User reviews for Google Cloud Bigtable suggest enhancements in user support, interface customization, and automated backups. For Azure Cosmos DB, users indicate a need for better cost predictability, more straightforward query optimization, and easier integrations. The concerns for Azure Cosmos DB are more focused on cost management.

Ease of Deployment and Customer Service: Google Cloud Bigtable is praised for its straightforward deployment and reliable support, offering a smooth start for new users. Azure Cosmos DB, while also having strong deployment capabilities, receives mixed feedback on customer service, with some users seeking more proactive support. Google Cloud Bigtable's consistency in support gives it a slight advantage.

Pricing and ROI: Users value Google Cloud Bigtable for its more transparent and affordable pricing, leading to a favorable ROI. Azure Cosmos DB's higher costs are justified by its comprehensive feature set and performance but may impact ROI perception. Pricing and ROI considerations lean toward Google Cloud Bigtable for cost-conscious buyers.

To learn more, read our detailed Google Cloud Bigtable vs. Microsoft Azure Cosmos DB Report (Updated: October 2024).

Buyer's Guide

Google Cloud Bigtable vs. Microsoft Azure Cosmos DB

October 2024

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Categories and Ranking

Google Cloud Bigtable

Ranking in Managed NoSQL Databases

7th

Average Rating

8.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Microsoft Azure Cosmos DB

Ranking in Managed NoSQL Databases

1st

Average Rating

8.2

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

Database as a Service (DBaaS) (6th), NoSQL Databases (3rd), Vector Databases (5th)

Mindshare comparison

As of December 2024, in the Managed NoSQL Databases category, the mindshare of Google Cloud Bigtable is 7.9%, down from 9.7% compared to the previous year. The mindshare of Microsoft Azure Cosmos DB is 17.8%, down from 19.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Managed NoSQL Databases

Featured Reviews

Aakash Sharma

Senior Technical Architect at HCL Technologies

Great for streaming data and being a managed service is an advantage

Our primary use case is for analytics, analyzing the data sets and curing Bigtable is very user-friendly where streaming data is required. I think it's relatively easier to use than Ascentra. The fact that it's a managed service is an advantage. The cost of this product is too expensive.…

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Michael Calvin

CTO at Kinectify

Easy to integrate, has a shallow learning curve, and scales dynamically

Azure Cosmos DB is quick to adopt with a shallow learning curve. The average user can be operational within hours or days, handling small to medium data volumes. However, optimizing for ultra-high throughput scenarios involves a steeper learning curve, requiring substantial knowledge to master Azure Cosmos DB. Nonetheless, most users can leverage it as their operational data store with minimal effort. Our platform boasts several extensive language model features, particularly around summarization capabilities. We use vector searching in Azure Cosmos DB to facilitate the retrieval of an augmented generation model with our LLM implementation. It's a standard RAG implementation using Azure Cosmos DB. Compared to other options, a key advantage of vector indexing in Azure Cosmos DB is the ability to query documents alongside vectors. This pinpoints the precise information required for RAG in our LLM solution, granting us greater flexibility than vector searching in other Azure services. We integrated the vector database with the Azure OpenAI service for our LLM solution. The Azure AI services were simple to integrate with the vector database. There was a slight learning curve, especially as we were on the private preview of vector searching. This led to some hiccups with our existing database configurations, specifically regarding continuous backup. We couldn't enable continuous backup and vector searching simultaneously. However, this was solely due to our participation in the preview, and I'm confident this issue won't persist in the general availability release. Azure Cosmos DB is fantastic for searching large amounts of data when the data is within a single partition. Over the last two weekends, we ingested over 400 gigabytes of data into our Azure Cosmos DB database and saw no change in querying performance compared to when our database was only 20 gigabytes in size. This is impressive and powerful, but the scope is limited to those partition queries. The first benefit we've seen is increased developer productivity. Azure Cosmos DB is an easy database to work with. Its schema-less nature allows us to iterate quickly on our platform, develop new features, and store the associated data in Azure. Developers find it easy to use, eliminating the need for object-relational mapping tools and other overhead. Geographic replication and the ability to scale geographically is another advantage. This is challenging with other databases, even other NoSQL databases, but Azure Cosmos DB makes it easy. Cost optimization is a major benefit as well. We've been able to run our platform at a fraction of the infrastructure cost our customers incur when integrating with us. This allows us to focus resources on feature development and platform building rather than infrastructure maintenance. Azure Cosmos DB helped reduce the total cost of ownership. We don't need DBAs, system administrators, or typical IT staff to run the infrastructure because we can use Azure Cosmos DB as a platform or a software-as-a-service data storage solution. This makes the total cost of ownership significantly lower than any comparable solution using relational databases or other NoSQL solutions like MongoDB. We enable auto-scaling on all of our Azure Cosmos DB resources, which helps us achieve cost optimizations.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The most valuable feature is the backup and replication service."

"The solution is very convenient."

"Scalability-wise, I rate the solution a ten out of ten."

"It's very user-friendly where streaming data is required."

"Bigtable is faster than other competitors in the market. It helps us collate all the data, and the security features are great. The latency is low, and the computation speed is fantastic. Bigtable is also a managed service, so you don't have to worry about anything aside from analyzing the data ingested."

"Stability-wise, it is a simple solution. I rate the solution's stability a ten out of ten."

"The biggest benefit it offers is scalability. It's easier to work with concurrency and updating data."

"The ability to scale automatically is very valuable. Additionally, multi-region support automatically synchronizing to a different region for multi-region applications is a cool feature. It's more of a lift with other databases to configure that extra region and set up replication, even if it's on the cloud. With Azure, it's just a button click. It's that simple."

"It's highly scalable and supports consistency, security, and multiple security options."

"I like the scalability. There aren't any constraints for posting in the geolocation. I also like the SQL architecture."

"It is non-SQL and helps to manage and manipulate data from the coding, rather than direct data and complex queries."

"The most valuable features for our organization with Azure Cosmos DB are multi-master capability for applications, automatic failover ensuring high availability, scalability, support for multiple data models, and low-latency access."

"The global synchronization feature of Azure Cosmos DB stands out as the most valuable for me."

"The solution is extremely user-friendly and easy to navigate."

More Microsoft Azure Cosmos DB pros

Cons

"The lagging problem of the product I face is an area of concern where improvements are required."

"This product needs better security and transparency, and the price should be reduced."

"Improvement should be made as per customer recommended and requirements."

"I've used Bigtable for about three or four years."

"The cost of this product is too expensive."

"When it comes to complex queries, a user can't get any help from a drop-down box and pick columns. It would be great if some improvements could be made in the aforementioned area concerning the solution."

"If you want to bring the data from AWS, you must pay data egress costs. That's a pain point."

"Because there is no local way of doing things, Azure Cosmos DB will always be considered expensive."

"Slight enhancements in integration interfaces, expanded dashboard functionalities, and broader use-case support would be beneficial."

"The integration of the on-premise solution with the cloud can be difficult sometimes."

"Firstly, having a local development emulator or simulator for Azure Cosmos DB would be beneficial. It would be very handy to have a Docker container that developers can use locally."

"Azure Cosmos DB for NoSQL has a less developed interface and fewer SQL commands than MongoDB, and its community support is also smaller."

"There are multiple approaches to implementing multitenant architecture on Azure Cosmos DB, but there is still no single or best-recommended approach when you have a big variance in the size of your tenants. That is something that still needs to be worked on."

"The support tickets are not cheap."

More Microsoft Azure Cosmos DB cons

Pricing and Cost Advice

Information not available

"Azure is a pay as you go subscription."

"The pricing and licensing model was initially difficult to understand, but as soon as I learned what was going on and how it was priced, it was pretty easy."

"The solution is a bit on the expensive side."

"From a startup point of view, it appears to be expensive. If I were to create my startup, it would not have the pricing appeal compared to the competition, such as Supabase. All those other databases are well-advertised by communities. I know there is a free tier with Azure Cosmos DB. It is just not well advertised."

"Cosmos DB is a managed offering, so its cost is understandably higher."

"Cosmos DB gave us three accounts for $400. We pay according to the usage."

"The Cosmos DB pricing model, initially quite complicated, became clear after consulting with Azure Advisor, allowing us to proceed with confidence."

"Cosmos DB's pricing structure has significantly improved in recent months, both in terms of its pricing model and how charges are calculated."

More Microsoft Azure Cosmos DB pricing and cost advice

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Top Industries

By visitors reading reviews

Computer Software Company

14%

University

12%

Financial Services Firm

10%

Retailer

Computer Software Company

13%

Comms Service Provider

11%

Financial Services Firm

11%

Retailer

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about Google Cloud Bigtable?

Scalability-wise, I rate the solution a ten out of ten.

See all answers

What needs improvement with Google Cloud Bigtable?

The lagging problem of the product I face is an area of concern where improvements are required. In general, the performance of the product needs improvement.

See all answers

What is your primary use case for Google Cloud Bigtable?

When a client gives our organization a project where they need a dashboard for their company, they provide us with some data from their database, which is usually presented in Google Cloud Bigtable...

See all answers

What do you like most about Microsoft Azure Cosmos DB?

The initial setup is simple and straightforward. You can set up a Cosmos DB in a day, even configuring things like availability zones around the world.

See all answers

What is your experience regarding pricing and costs for Microsoft Azure Cosmos DB?

Cosmos DB is a managed offering, so its cost is understandably higher. However, the value it provides aligns with its price, especially considering the discounts we receive. By purchasing reserved ...

See all answers

What needs improvement with Microsoft Azure Cosmos DB?

Cosmos DB has a couple of areas for improvement. Firstly, the lack of multi-collection joins is a significant limitation. Secondly, Azure Synapse Link, their data warehousing and synchronization fe...

See all answers

Comparisons

Amazon DynamoDB vs Google Cloud Bigtable

Compared 43% of the time

Amazon Timestream vs Google Cloud Bigtable

Compared 26% of the time

More Google Cloud Bigtable Competitors

Amazon Neptune vs Microsoft Azure Cosmos DB

Compared 18% of the time

Amazon DynamoDB vs Microsoft Azure Cosmos DB

Compared 12% of the time

Neo4j AuraDB vs Microsoft Azure Cosmos DB

Compared 12% of the time

Chroma vs Microsoft Azure Cosmos DB

Compared 11% of the time

Faiss vs Microsoft Azure Cosmos DB

Compared 6% of the time

More Microsoft Azure Cosmos DB Competitors

Product Reports

Buyer's Guide

Managed NoSQL Databases

November 2024

Download Google Cloud Bigtable product report

Buyer's Guide

Microsoft Azure Cosmos DB

November 2024

Download Microsoft Azure Cosmos DB product report

Also Known As

No data available

Microsoft Azure DocumentDB, MS Azure Cosmos DB

Learn More

Google

Microsoft

Overview

Cloud Bigtable is Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Azure Cosmos DB is a fully managed NoSQL and vector database service built for AI-powered apps at any scale. It fuels apps with high-performance, distributed computing over massive volumes of NoSQL and vector data. Developers can start small and pay for only what they use with serverless computing, and enhance the solution seamlessly with unlimited dynamic autoscale, SLA-backed 99.999 percent availability and <10ms latency. Azure Cosmos DB lets developers build applications with the languages and frameworks of their choice, such as Python, Node.js, and Java. These unique benefits make Azure Cosmos DB a great fit for responsive, high-performance customer-facing apps that are secure and highly available. Some popular use cases for Azure Cosmos DB are AI assistants, real-time transactional applications, IoT and smart products, personalization and recommendations, as well as SaaS applications.

Sample Customers

Cognite, Dow Jones, Loblaw Digital

TomTom, KPMG Australia, Bosch, ASOS, Mercedes Benz, NBA, Zero Friction, Nederlandse Spoorwegen, Kinectify

Buyer's Guide

Google Cloud Bigtable vs. Microsoft Azure Cosmos DB

October 2024

Free Report: Google Cloud Bigtable vs. Microsoft Azure Cosmos DB

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