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CHALLENGES

MongoDB vs. Couchbase: Performance, Scalability & Deployment Challenges

Customers migrating from MongoDB to Couchbase—whether on-premises or in the cloud—frequently encounter performance bottlenecks, scaling issues, and integration challenges. Couchbase vs MongoDB benchmark comparisons reveal that MongoDB often struggles with high-performance workloads as data volume grows, requiring additional tools to achieve full functionality. Businesses also report difficulties with mobile deployments and the limitations of MongoDB’s proprietary query language, making it harder to optimize database performance efficiently.

CHALLENGE #1
An unfamiliar query language

MongoDB's proprietary query language is far more complex and less well known than SQL.

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CHALLENGE #2
Inflexible architecture

MongoDB leaves data at risk because it’s inflexible and can’t adapt to modern workloads.

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CHALLENGE #3
Performance at scale

MongoDB’s performance degrades rapidly as the cluster size or number of users increases.

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CHALLENGE #4
Limited analytics offering

For scalable, real-time analytics MongoDB customers need to export to another platform.

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CHALLENGE #5
Mobile and edge computing

MongoDB has deprecated their mobile tooling, including Device Sync, Edge Server, and Device SDKs/Realm SDKs.

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CHALLENGE #6
AI-powered applications

MongoDB Atlas supports Lucene-based vector search only in the cloud, while Couchbase offers native vector support in the cloud and at the edge on mobile devices.

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FEATURES

Key features of Couchbase vs. MongoDB

  • What’s included
  • JSON flexibility
  • Built-in managed cache
  • Mobile, edge, and peer-to-peer sync
  • SQL
  • Native full-text search
  • Native vector search
  • XDCR master-master replication
  • Automatic sharding
  • Masterless shared-nothing architecture
  • ACID transactions
  • Multi-dimensional scaling
  • Vector search on mobile
  • Columnar storage engine
  • Multisource, zero-ETL ingestion
  • Write-back, real-time analytics to source cluster
  • Couchbase
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  • MongoDB
  • BSON
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  • Lucene-based and only available in Atlas
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CUSTOMERS

What customers are saying

  • “We see very consistent 500 microsecond response times from Couchbase even at very large scale.”
    Technical Lead, Cisco
    100B+ user sessions per year
    500 microsecond response times
  • "We found that the replication technology across data centers for Couchbase was superior, especially for large workloads."
    Claus Moldt, CIO, FICO
    <1 ms response times
    24x365 application uptime
  • “With less than half the servers, we can increase performance and gain a much better scalable architecture.”
    Amir Ish-Shalom, Sr. Director of Operations, Viber
    15 billion call and message events/day
    60% reduction in total servers
Code snippet

Comparison of equivalent queries in Couchbase SQL++ and MongoDB's MQL


/* equivalent to the Mongo example */
SELECT SUM(value * volume) AS val, symbol
FROM   db.stocks
WHERE  symbol IN ( "AAPL", "GOOG" ) AND value > 0
GROUP  BY symbol
ORDER  BY val DESC, symbol ASC



// equivalent to the SQL++ example
db.stocks.aggregate([
	 { "$match": {
	 	 "$and": [
	 	 	 {"symbol": {
	 	 	 	 "$in": [
	 	 	 	 "AAPL",
	 	 	 	 "GOOG"]}},
	 	 	 { "value": {
	 	 	 "$gt": 0 }}]}},
	 { "$group": {
	 	 "_id": {
	 	 	 "symbol": "$symbol" },
	 	 "sum(value * volume)": {
	 	 	 "$sum": {
	 	 	 	 "$multiply": [
	 	 	 	 	 "$value",
	 	 	 	 	 "$volume"]}}}},
	 { "$project": {
	 	 "_id": 0,
	 	 "sum(value * volume)": "$sum(value * volume)",
	 	 "symbol": "$_id.symbol"}}
	 { "$sort": {
	 	 "sum(value * volume)": -1,
	 	 "symbol": 1 }}]})
DBaaS performance report

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Resources

Learn more about how Couchbase compares to MongoDB

WHITEPAPER
Couchbase vs. MongoDB for scale-out and high availability
Get the paper
BLOG
Database replication – MongoDB vs. Couchbase
Read the blog
VIDEO
Migrating from MongoDB Atlas Device Sync to Couchbase Mobile
Watch now
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