Amazon Keyspaces vs Google Cloud Bigtable comparison

Amazon Web Services (AWS) and Google are both solutions in the Managed NoSQL Databases category. Amazon Web Services (AWS) is ranked #12, while Google is ranked #10 with an average rating of 9.0. Amazon Web Services (AWS) holds a 4.5% mindshare in MND, compared to Google’s 5.2% mindshare. Additionally, 100% of Google users are willing to recommend the solution.

Amazon Keyspaces

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Google Cloud Bigtable

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Amazon Keyspaces

Google Cloud Bigtable

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Executive SummaryUpdated on Jan 15, 2026

Google Cloud Bigtable and Amazon Keyspaces are fully managed databases designed for large-scale applications. Google Cloud Bigtable seems to have an edge in scalability and response time, while Amazon Keyspaces has advantages in compatibility with existing Amazon services.

Features: Google Cloud Bigtable offers automatic scalability, high availability, and strong performance in large data environments. It excels in real-time analytics, handling analytical tasks efficiently. Amazon Keyspaces provides compatibility with Apache Cassandra workloads, automatic data replication across AWS regions, and integrates with AWS security services, facilitating seamless adaptation of existing Cassandra applications.

Ease of Deployment and Customer Service: Google Cloud Bigtable offers a straightforward deployment process with extensive documentation and support within Google's platform. Amazon Keyspaces ensures a smooth deployment experience, made notable by its comprehensive integration with other AWS services, allowing seamless transitions and operations.

Pricing and ROI: Google Cloud Bigtable's pricing model is based on usage, offering potential cost efficiency for extensive data operations. Amazon Keyspaces utilizes on-demand pricing with options for optimal setups, affecting initial ROI. Bigtable may present lower operational costs for analytical workloads, while Keyspaces provides benefits for existing AWS customers through integration.

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Review summaries and opinions

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

Categories and Ranking

Amazon Keyspaces

Ranking in Managed NoSQL Databases

12th

Average Rating

0.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Google Cloud Bigtable

Ranking in Managed NoSQL Databases

10th

Average Rating

8.6

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

Non-Relational Databases (6th)

Mindshare comparison

As of January 2026, in the Managed NoSQL Databases category, the mindshare of Amazon Keyspaces is 4.5%, down from 6.3% compared to the previous year. The mindshare of Google Cloud Bigtable is 5.2%, down from 6.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Managed NoSQL Databases Market Share Distribution
Product	Market Share (%)
Google Cloud Bigtable	5.2%
Amazon Keyspaces	4.5%
Other	90.3%

Managed NoSQL Databases

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Akash Shanker

Team Lead at a financial services firm with 5,001-10,000 employees

Consistent performance and seamless cloud integration enhance analytics capabilities while reducing management complexity

One point for improvement in Google Cloud Bigtable is that people have confusion in mapping. There are many similar products available, and Google has managed services for similar products as well. It would be easier if the journey of knowing when to use Google Cloud Bigtable versus other Cloud SQL and alternates such as Cloud Spanner is made clearer for users. Regarding additional functionality for Google Cloud Bigtable, I am uncertain if LLMs can be integrated or if Google Cloud Bigtable can act as a vector store for LLM-specific use cases where we are interacting or using generative AI capabilities.

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Top Industries

By visitors reading reviews

No data available

Financial Services Firm

10%

Computer Software Company

Manufacturing Company

Educational Organization

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	6
Large Enterprise	3

Questions from the Community

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What do you like most about Google Cloud Bigtable?

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

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What needs improvement with Google Cloud Bigtable?

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What is your primary use case for Google Cloud Bigtable?

My main use case for Google Cloud Bigtable is mainly for advertisement-related analytics-related use cases.

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Comparisons

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Compared 55% of the time

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Compared 14% of the time

Amazon Timestream vs Amazon Keyspaces

Compared 7% of the time

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Microsoft Azure Cosmos DB vs Google Cloud Bigtable

Compared 25% of the time

Amazon DynamoDB vs Google Cloud Bigtable

Compared 18% of the time

MongoDB Enterprise Advanced vs Google Cloud Bigtable

Compared 15% of the time

Timescale vs Google Cloud Bigtable

Compared 7% of the time

Amazon Timestream vs Google Cloud Bigtable

Compared 7% of the time

More Google Cloud Bigtable Competitors

Product Reports

Buyer's Guide

Managed NoSQL Databases

January 2026

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Buyer's Guide

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January 2026

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Also Known As

Amazon Managed Apache Cassandra Service (MCS)

Google BigTable

Overview

Amazon Keyspaces (for Apache Cassandra) is a scalable, highly available, and managed Apache Cassandra–compatible database service. With Amazon Keyspaces, you can run your Cassandra workloads on AWS using the same Cassandra application code and developer tools that you use today. You don’t have to provision, patch, or manage servers, and you don’t have to install, maintain, or operate software. Amazon Keyspaces is serverless, so you pay for only the resources you use and the service can automatically scale tables up and down in response to application traffic. You can build applications that serve thousands of requests per second with virtually unlimited throughput and storage. Data is encrypted by default and Amazon Keyspaces enables you to back up your table data continuously using point-in-time recovery. Amazon Keyspaces gives you the performance, elasticity, and enterprise features you need to operate business-critical Cassandra workloads at scale.

Amazon Web Services (AWS)

Google Cloud Bigtable provides large data capacity, fast computation speed, and robust security for efficient data management. It supports seamless querying and integration, making it suitable for users transitioning to the cloud.

Google Cloud Bigtable is a managed service offering that facilitates efficient data handling through its high-performance capabilities and compatibility with other NoSQL databases. It is highly valued for its ability to manage and analyze large datasets, offering features like backup and replication, and is known for being faster than many competitors. Despite its strengths, users express concerns over its pricing, querying complexity, occasional performance lag, and difficulty in choosing between Bigtable and other services. There's also interest in its potential for integration with emerging technologies like LLMs for generative AI applications.

What are the key features of Google Cloud Bigtable?

Large Data Capacity: Supports immense volumes of data, essential for big data initiatives.
Seamless Querying: Queries large datasets with efficiency and speed.
Backup and Replication: Provides data reliability and easy recovery.
Low Latency: Ensures fast response times for queries and operations.
High Computation Speed: Offers rapid data processing capabilities.

What benefits should users look for in reviews?

Data Security: Provides robust security for sensitive data.
Ease of Analysis: Simplifies the process of collating and analyzing data.
Cloud Integration: Compatible with other NoSQL databases, aiding cloud transitions.
Fast Performance: Noted for being quicker than many alternatives.

Industries implement Google Cloud Bigtable for data management tasks such as managing large datasets, resolving production issues, and generating insights through dashboards. It is used in advertising analytics, client data evaluation in Power BI reports, and some automotive clients employ it for specialized needs, integrating business data into Google's ecosystem for efficient analysis.

Google

Sample Customers

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers

Cognite, Dow Jones, Loblaw Digital

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