{"id":1235,"date":"2018-02-06T02:02:09","date_gmt":"2018-02-06T10:02:09","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/couchbase-server-vs-cosmosdb\/"},"modified":"2018-02-06T02:02:09","modified_gmt":"2018-02-06T10:02:09","slug":"couchbase-server-vs-cosmosdb","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/couchbase-server-vs-cosmosdb\/","title":{"rendered":"Comparing Couchbase vs CosmosDB"},"content":{"rendered":"\n

Microsoft has generated a lot of buzz since the launch of CosmosDB. It is basically a rebranding of Amazon DocumentDB with some new cool features. Let\u2019s go a little deeper on it and explore its strategy, documentation, what developers have been talking about and how does it compares with Couchbase Server.<\/span><\/p>\n\n\n\n

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One Database to rule them all?<\/b><\/h3>\n\n\n\n

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In simple words, Microsoft claims that CosmosDB is a NoSQL database able to do literally everything<\/em>: It is a Document database, Columnar storage, a Key-Value Store and a Graph Database. All achieved thanks to an abstraction of the data format called atom-record-sequence (ARS).<\/span><\/p>\n\n\n\n

A good sign of Microsoft\u2019s work is how data is differently organized according to each model. First, you have to choose the API you would like to use ( SQL, MongoDB API, Microsoft Azure Table, Cassandra or Gremlin) and stick with it as it can\u2019t be changed later. Currently, you can still try to access some models through DocumentDB API. that was what gave me some hints of how <\/span>CosmosDB uses internally a decorated JSON format<\/span><\/a> to store its data.<\/span><\/p>\n\n\n\n

It looks like Microsoft wants to compete with most of the NoSQL databases out there, which is a really risky strategy as we might have passed the gold era of a single database solution for everything.<\/em> There are huge benefits of choosing specialized storages, and this is the path most of the applications have been following right now with the rise of <\/span>polyglot persistences<\/span><\/a>. \u00a0An all-in-one<\/em> solution like CosmosDB might be good for low-demanding applications, but all those abstractions come with a cost and will ultimately impact simplicity, performance and be feature limited.<\/span><\/p>\n\n\n\n

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Couchbase vs CosmosDB – Comparing Apples with \u201cApples\u201d<\/b><\/h3>\n\n\n\n

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I will try to limit my comparison with CosmosDB focusing most on scenarios that make sense to compare both technologies. The table below tries to show some of the differences side-by-side:<\/span><\/p>\n\n\n\n

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Feature<\/b><\/td>\nCosmosDB<\/b><\/td>\nCouchbase Server<\/b><\/td>\n<\/tr>\n
Licensing<\/span><\/td>\n\n
    \n
  • Proprietary<\/span><\/li>\n<\/ul>\n<\/td>\n
\n
Type<\/span><\/td>\n\n
    \n
  • Key-Value Store<\/span><\/li>\n
  • Document Database<\/span><\/li>\n
  • Graph Database<\/span><\/li>\n
  • Columnar storage<\/span><\/li>\n<\/ul>\n<\/td>\n
\n
Model<\/span><\/td>\n\n\n
Search<\/span><\/td>\n\n
    \n
  • Azure Search<\/span><\/li>\n<\/ul>\n<\/td>\n
\n
Indexing<\/span><\/td>\n\n\n
Data Integrity<\/span><\/td>\n\n
    \n
  • Strongly Consistent<\/span><\/li>\n
  • Bounded-staleness<\/span><\/li>\n<\/ul>\n
      \n
    • Session (default)<\/span><\/li>\n
    • Consistent Prefix<\/span><\/li>\n
    • Eventually Consistent<\/span><\/li>\n<\/ul>\n<\/td>\n
\n
Scalability<\/span><\/td>\nHighly Scalable<\/span><\/td>\nHighly Scalable<\/span><\/a><\/td>\n<\/tr>\n
Mobile<\/span><\/td>\n\n\n
Deployment<\/span><\/td>\n\n
    \n
  • Azure Only, fully managed<\/span><\/li>\n
  • Development version available only on Windows<\/span><\/li>\n<\/ul>\n<\/td>\n
\n
Locking<\/span><\/td>\n\n
    \n
  • Optimistic Locking<\/span><\/li>\n
  • Pessimistic Locking<\/span><\/li>\n<\/ul>\n<\/td>\n
\n
Backup & Restore<\/span><\/td>\n\n\n
Querying<\/span><\/td>\n\n
    \n
  • Querying is made according to the chosen API, and each API has different limitations<\/span><\/li>\n<\/ul>\n<\/td>\n
\n
Data Center Replication<\/span><\/td>\n\n
    \n
  • Push-button global Bidirectional replication<\/span><\/li>\n<\/ul>\n<\/td>\n
\n
Throttling<\/span><\/td>\n\n
    \n
  • Only by increasing RCUs<\/span><\/li>\n<\/ul>\n<\/td>\n
\n
Administration Interface<\/span><\/td>\n\n
    \n
  • Feature-rich administration interface;<\/span><\/li>\n
  • Provide a few endpoints to automate some tasks<\/span><\/li>\n
  • Some features aren\u2019t well documented<\/span><\/li>\n<\/ul>\n<\/td>\n
\n
Sharding<\/span><\/td>\n\n
    \n
  • Partitioning is made automatically but you are required to pick a partition key.<\/span><\/li>\n<\/ul>\n<\/td>\n
Sharding is automatically done under the covers<\/span><\/a><\/td>\n<\/tr>\n
Security<\/span><\/td>\n\n
    \n
  • Provided by normal Azure security measures<\/span><\/li>\n<\/ul>\n<\/td>\n
\n
Architecture<\/span><\/td>\n\n
    \n
  • Unknown<\/span><\/li>\n<\/ul>\n<\/td>\n
\n
Integrations<\/span><\/td>\n\n
    \n
  • Spark, Hadoop<\/span><\/li>\n
  • Other Azure Services<\/span><\/li>\n
  • MongoDB Connector<\/span><\/li>\n
  • Cassandra<\/span><\/li>\n
  • Gremlin<\/span><\/li>\n<\/ul>\n<\/td>\n
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