Google Cloud BigTable vs. Google Cloud Spanner

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Cloud BigTable
Score 9.4 out of 10
N/A
Google's Cloud Bigtable is a fully managed, scalable NoSQL database service for large analytical and operational workloads with up to 99.999% availability.
$0.03
per month
Google Cloud Spanner
Score 5.6 out of 10
N/A
Google Cloud Spanner is a cloud database-as-a-service product offered as a service on Google Cloud Platform (GCP).N/A
Pricing
Google Cloud BigTableGoogle Cloud Spanner
Editions & Modules
Backup Storage
$0.026
per month per GB
HDD storage
$0.026
per month per GB
SSD storage
$0.17
per month per GB
Nodes
$0.65/hour
per month per node (minimum 1 nodes)
No answers on this topic
Offerings
Pricing Offerings
Cloud BigTableGoogle Cloud Spanner
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Google Cloud BigTableGoogle Cloud Spanner
Considered Both Products
Cloud BigTable

No answer on this topic

Google Cloud Spanner
Chose Google Cloud Spanner
At that point, we were looking at something [that] can hold our relational database, [...] provide stable connection, and maintain high ACID transition. BigTable is for nonrelational database so it was out of our [sight] very quickly. BigQuery is a data warehouse that can hold …
Features
Google Cloud BigTableGoogle Cloud Spanner
Database-as-a-Service
Comparison of Database-as-a-Service features of Product A and Product B
Google Cloud BigTable
9.2
2 Ratings
8% above category average
Google Cloud Spanner
7.8
2 Ratings
9% below category average
Automatic software patching10.02 Ratings8.82 Ratings
Database scalability9.02 Ratings8.82 Ratings
Automated backups9.02 Ratings10.01 Ratings
Database security provisions9.02 Ratings5.82 Ratings
Monitoring and metrics8.02 Ratings5.82 Ratings
Automatic host deployment10.01 Ratings7.62 Ratings
Best Alternatives
Google Cloud BigTableGoogle Cloud Spanner
Small Businesses
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
Medium-sized Companies
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
Enterprises
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
IBM Cloudant
IBM Cloudant
Score 7.4 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Google Cloud BigTableGoogle Cloud Spanner
Likelihood to Recommend
9.0
(1 ratings)
7.4
(2 ratings)
Usability
9.0
(1 ratings)
-
(0 ratings)
Support Rating
9.0
(1 ratings)
-
(0 ratings)
User Testimonials
Google Cloud BigTableGoogle Cloud Spanner
Likelihood to Recommend
Google
It works great for any use case that requires high throughput for reads and writes, for key-value kinda data. This enables you to use it for usecases where you need to retain data for a long term or even short term but then use it in pipelines to enrich data, sync states between backend and frontend or to quickly lookup say a user.
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Google
Google Cloud Spanner is suited for limitless horizontal scaling while maintaining strong consistency which needs to support ACID. NoSQL databases work in scaling but no ACID support. RDBMS support ACID, but horizontal scaling is not as great. The API it provides result in some limitations to related areas of the code, such as connection pools or database linking framework. So high # of connection pools can vary.
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Pros
Google
  • Analytics: is at Google's heart. No on can beat Google in this space and BigTable is one of its implementation of this. The insights you gain from BigTable are simply usable in your day to day activities and can help you make real difference.
  • Speed: Processing TBs and PBs of data under minutes needs real efficient platform which is capable of doing much more than just processing data. All this data cannot be processed by a single machine, but rather huge pairs of machines working in conjuction with each other. BigTable's implementation is one of the finest and allows you achieve great speeds!
  • Interface: is great. Google has segregated required task under logically placed buttons which takes no time by users to understand and get habituated.
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Google
  • Super high availability
  • Scales automatically
  • High standard SLA
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Cons
Google
  • Global replication
  • Complete SQL support
  • Size limit of 1MB
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Google
  • Support for Views
  • Support for more databases (schemas).
  • More index types that can be supported (Functional)
  • Backups (ie table/data backup) if data is deleted or truncate by accident.
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Usability
Google
For big IT firms like us, data is very important and it only holds its value if it can make sense to us. Therefore, Bigtable's usability is priceless when it comes to decision making based on data.
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Google
No answers on this topic
Support Rating
Google
Google provides premium support services for BigTable which is absolutely blazing fast similar to Bigtable's performance.
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Google
No answers on this topic
Alternatives Considered
Google
As a hosted solution, that can be managed easily from the Google cloud platform, it enables the teams to think about business use cases vs thinking about the management of the database itself. It is easily to scale it up when you need more throughput or storage. This keeps the developers and the product folks happy.
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Google
At that point, we were looking at something [that] can hold our relational database, [...] provide stable connection, and maintain high ACID transition. BigTable is for nonrelational database so it was out of our [sight] very quickly. BigQuery is a data warehouse that can hold huge amount of data but not ideal for transition. AWS RDS is [...] similar to Spanner but because most of our services are already on GCP, so we went with Spanner.
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Return on Investment
Google
  • Building new features that can leverage storage on the edge
  • Realtime decision making
  • Data enrichment
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Google
  • Backups specifically if transactional data is deleted. Restoring made us lose time.
  • Sharding on Horizontal level was quick and easy. Deployment and increasing nodes is easy
  • Large dataset handling.
  • ACID compliance
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