CouchDB vs Google BigQuery

• It can replicate and sync with web browsers via PouchDB. This lets you keep a synced copy of your database on the client-side, which offers much faster data access than continuous HTTP requests would allow, and enables offline usage.
• Simple Map/Reduce support. The M/R system lets you process terabytes of documents in parallel, save the results, and only need to reprocess documents that have changed on subsequent updates. While not as powerful as Hadoop, it is an easy to use query system that's hard to screw up.
• Sharding and Clustering support. As of CouchDB 2.0, it supports clustering and sharding of documents between instances without needing a load balancer to determine where requests should go.
• Master to Master replication lets you clone, continuously backup, and listen for changes through the replication protocol, even over unreliable WAN links.

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• Huge plus point if you have idea running SQL scripts.
• The ability to store and manage multiple data warehouses is a big plus point which helps a lot for growing businesses.
• Easy integration with tools like Data Studio and Google Analytics which provides great data warehouse and data management solutions.

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• NoSQL DB can become a challenge for seasoned RDBMS users.
• The map-reduce paradigm can be very demanding for first-time users.
• JSON format documents with Key-Value pairs are somewhat verbose and consume more storage.

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• One issue with Google Cloud Storage is its price. For one to have that premium Google Cloud Storage, for the purpose of massive storage, he/she must have adequate cash. Otherwise, Google Cloud Storage is a safe and perfect online storage platform.
• The only thing that can come to mind that would be annoying with this software was that sometimes when trying to share files on the Cloud with coworkers, it would just not share at all, or there would be a massive delay in when I shared them and when they received them. Other than that though, everything is perfect with this.

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• It has saved us hours and hours of coding.
• It is has taught us a new way to look at things.
• It has taught us patience as the first few weeks with CouchDB were not pleasant. It was not easy to pick up like MongoDB.

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• Google BigQuery has had enormous impact in terms of ROI to our business, as it has allowed us to ease our dependence on our physical servers, which we pay for monthly from another hosting service. We have been able to run multiple enterprise scale data processing applications with almost no investment
• Since our business is highly client focused, Google Cloud Platform, and BigQuery specifically, has allowed us to get very granular in how our usage should be attributed to different projects, clients, and teams.
• Plain and simple, I believe the meager investments that we have made in Google BigQuery have paid themselves back hundreds of times over.

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