Apache CouchDB vs. Google Cloud Datastore

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
CouchDB
Score 6.0 out of 10
N/A
Apache CouchDB is an HTTP + JSON document database with Map Reduce views and bi-directional replication. The Couch Replication Protocol is implemented in a variety of projects and products that span computing environments from globally distributed server-clusters, over mobile phones to web browsers.N/A
Google Cloud Datastore
Score 7.1 out of 10
N/A
Google Cloud Datastore is a NoSQL "schemaless" database as a service, supporting diverse data types. The database is managed; Google manages sharding and replication and prices according to storage and activity.N/A
Pricing
Apache CouchDBGoogle Cloud Datastore
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
CouchDBGoogle Cloud Datastore
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
Apache CouchDBGoogle Cloud Datastore
Considered Both Products
CouchDB
Chose CouchDB
Open Source, and freely able to install it on any OS you desire (the big 3, anyways) CouchDB was selected for that, it's early-adoption of JSON and its mobile-friendly environment. Also, I have used it off and on in various non-professional projects, and it was really one of …
Chose CouchDB
Compared to MongoDB, CouchDB's Map-Reduce paradigm poses a steeper learning curve for SQL users. However, CouchDB's master-master replication is an advantage of implementing a load-balanced solution.
Even though, currently, CouchDB has strong community support, as an open …
Chose CouchDB
MongoDB and CouchDB are both document stores, but their concurrency models and ability to scale are very different. MongoDB cannot replicate / shard over unreliable links and network partitions have been the cause of data loss in the past. MongoDB has an easier query language …
Chose CouchDB
It has been 5+ years since we chose CouchDB. We looked an MongoDB, Cassandra, and probably some others. At the end of the day, the performance, power potential, and simplicity of CouchDB made it a simple choice for our needs. No one should use just because we did. As I said …
Chose CouchDB
S3 blew this out of the water, we can get over 30 files a second, almost no failures, auto backed up, don't need our own server, and a much simpler interface with PHP Laravel.
Chose CouchDB
We looked at MongoDB and Firebase. MongoDB gives us the best working db engine with a very intuitive design. However, it does not work as well offline. Firebase was extremely hard to create searching and indexing. Using a third-party to search didn't work for us or at least it …
Chose CouchDB
Developing spring boot apps with Couchbase using Spring Data JPA really solves complexity of programming.
Chose CouchDB
I have briefly used MongoDB in other products, and it proved that it had better integration capabilities with Ruby on Rails and node.js software platforms, more than CouchDB. But I never had the chance to actually replace CouchDB with MongoDB in the current product to see what …
Chose CouchDB
It stacks up well against Mongo DB. Mongo DB definitely has more marketing and developer and customer mindshare because it is so widely known.
Chose CouchDB
CouchbaseDB is essentially faster with more options but of course with a cost. Cloudant is the hosted option with a better security schema.
Google Cloud Datastore
Chose Google Cloud Datastore
As stated before, we eventually chose Google Cloud Datastore because we were already leveraging other Google Cloud services like VMs, Cloud Runs, logging etc. MySQL and MongoDB were possible alternatives, but we preferred to lock in to the Google ecosystem.
Chose Google Cloud Datastore
We selected Google Cloud Datastore as one of our candidates for our NoSQL data is because it is provided by Google Cloud, which fits our needs. Most of our infrastructure is on Google Cloud, so when we think about the NoSQL database, the first thing we thought about is Google …
Chose Google Cloud Datastore
If deploying an application in Google Cloud Platform, using Google Cloud Datastore is a no brainer because of the simplicity of setup. Other options would require more setup and configuration, and do not come with the same level of guaranteed uptime as Google Cloud Datastore. …
Features
Apache CouchDBGoogle Cloud Datastore
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
Apache CouchDB
7.9
Ratings
8% below category average
Google Cloud Datastore
8.4
Ratings
2% below category average
Performance8.00 Ratings10.00 Ratings
Availability8.50 Ratings7.00 Ratings
Concurrency8.50 Ratings9.00 Ratings
Security6.00 Ratings9.00 Ratings
Scalability8.00 Ratings10.00 Ratings
Data model flexibility7.00 Ratings4.00 Ratings
Deployment model flexibility9.00 Ratings9.90 Ratings
Best Alternatives
Apache CouchDBGoogle Cloud Datastore
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
Apache CouchDBGoogle Cloud Datastore
Likelihood to Recommend
9.0
(0 ratings)
6.0
(0 ratings)
Likelihood to Renew
9.0
(0 ratings)
10.0
(0 ratings)
Usability
8.0
(0 ratings)
7.0
(0 ratings)
Implementation Rating
9.0
(0 ratings)
-
(0 ratings)
User Testimonials
Apache CouchDBGoogle Cloud Datastore
Likelihood to Recommend
It's good as a general JSON document store and basic map/reduce system. For more specialized tasks like message queuing, graph traversal, streaming metrics aggregation, or arbitrary table joins, I'd recommend another database.
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If you want a serverless NoSQL database, no matter it is for personal use, or for company use, Google Cloud Datastore should be on top of your list, especially if you are using Google Cloud as your primary cloud platform. It integrates with all services in the Google Cloud platform.
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Pros
  • Ease of install and setup.
  • Ease of syncing with another database. This was truly set it and forget it.
  • The REST API to read data. No additional drivers are needed to work with CouchDB.
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  • Automatically handles shards and replication.
  • Schema-less & NoSQL.
  • Fully managed.
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Cons
  • SUPER SLOW. We do tons of data and S3 and just using the file system were both way faster
  • Using views is too complex
  • Stores entire DB as 1 file, good luck when it becomes many TB
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  • It is hosted on GCP, which makes it harder if your company have multi-cloud strategy.
  • When you want to migrate to other cloud providers, there can be a caveat.
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Likelihood to Renew
As a highly distributed database system, CouchDB naturally has strong high availability with traffic load-balancing capability. It is also easy to scale and replicate data in a cluster for redundancy. However, there is still some room for query performance improvement in the future.
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For the amount of use we're getting from Google Cloud Datastore, switching to any other platform would have more cost with little gain. Not having to manage and maintain Google Cloud Datastore for over 4 years has allowed our teams to work on other things. The price is so low that almost any other option for our needs would be far more expensive in time and money.
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Usability
Couchdb is very simple to use and the features are also reduced but well implemented. In order to use it the way its designed, the ui is adequate and easy. Of course, there are some other task that can't be performed through the admin ui but the minimalistic design allows you to use external libraries to develop custom scripts
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The simple implementation, together with the Google Cloud dashboard that allows data inspection, editing and querying, makes Google Cloud Datastore a comprehensive choice when it comes to NoSQL databases.
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Implementation Rating
it support is minimal also hw requirements. Also for development, we can have databases replicated everywhere and the replication is automagical. once you set up the security and the rules for replication, you are ready to go. The absence of a model let you build your app the way you want it
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Alternatives Considered
Open Source, and freely able to install it on any OS you desire (the big 3, anyways) CouchDB was selected for that, it's early-adoption of JSON and its mobile-friendly environment. Also, I have used it off and on in various non-professional projects, and it was really one of the first exposure to databases in my career
Read full review
As stated before, we eventually chose Google Cloud Datastore because we were already leveraging other Google Cloud services like VMs, Cloud Runs, logging etc. MySQL and MongoDB were possible alternatives, but we preferred to lock in to the Google ecosystem.
Read full review
Return on Investment
  • Biggest impact on our business has been that CouchDB has been pretty invisible from a cost or issues perspective. It just works.
  • We use the Apache releases, so it's free. Of course there is a cost to "free" - we have invested time to become fluent in using and understanding CouchDB. But we feel the investment was well worth the effort and we have a solid, fundamental technology to our products that "just works".
  • There are some things we do - SaaS vs self-hosting - that have probably been kept simple by using CouchDB. Overall, we are extremely happy with CouchDB.
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  • It solves our NoSQL database problem.
  • It it highly scalable and available to meets our needs.
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