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See how Atlas and Capella compare in the DBaaS performance report
Critical MongoDB disadvantages and how Couchbase overcomes them
Challenge 1: Query complexity
Try SQL on NoSQLMongoDB
Because MongoDB has no declarative query language, querying and processing data in applications requires complex procedural logic. This leads to poor query performance and scalability.Couchbase
SQL++ gives developers and enterprises an expressive, powerful, and complete language for querying, transforming, and manipulating JSON data. You can develop engaging applications using a comprehensive and declarative query language on JSON documents.Challenge 2: Lack of database joins
JOIN clauseMongoDB
Lack of effective document JOIN in sharded collections can impose technical restrictions on the data model design. This results in unnecessary denormalization, data duplication, and complex application logic.Couchbase
Full support for ANSI joins allows developers to leverage the best of SQL for enterprise applications. You get comprehensive support for document JOINS and aggregation pushdown.Challenge 3: Difficult migration from RDBMS
Migrating from relational databasesMongoDB
MongoDB's proprietary query API results in a high learning curve for SQL developers and forces expensive rewrites of existing applications.Couchbase
SQL++ extends industry standard SQL to JSON. You can query JSON document data models similarly to the way you query legacy RDBMS applications.Couchbase extends ANSI SQL to support the
flexible schema of JSON
| MongoDB Query | Couchbase SQL++ |
|---|---|
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 }}]}
|
SELECT SUM(value * volume) AS val, symbol
FROM Â db.stocks
WHERE Â symbol IN ( "AAPL", "GOOG" ) AND value > 0
GROUP Â BY symbol
ORDER Â BY val DESC, symbol ASC
|
Webcasts: How to Uplevel From MongoDB™ for Better Scalability, Performance, and Architecture
Register NowWhy enterprises choose Couchbase over MongoDB
DirectTV
Today's viewers demand seamless experiences and constant innovation. Finding MongoDB difficult to use and scale, DirecTV chose Couchbase for unparalleled performance at scale, bidirectional cross datacenter replication to keep services available for viewers 24/7, and SQL++ for powerful queries.
Viber
Pushed to scale at a rate its MongoDB and Redis backend could no longer support, Viber switched its messaging platform to Couchbase. With Couchbase, Viber cut its servers by more than 50%, is robust enough to avoid downtime, and now supports close to a million operations per second and datasets with billions of records.
Nuance
Nuance, a speech recognition and imaging software company, had a monolithic all-Oracle environment that was expensive to scale and inflexible for varied data types. As it explored NoSQL, Nuance found MongoDB hard to manage. It chose Couchbase instead for easy, cost-effective performance at scale and bidirectional replication.
Staples
Staples needed to better manage B2B catalogs using 1.6 billion rules applied in real time. Staples tried MongoDB, but its inability to scale easily and affordably led to canceled projects. Couchbase not only enabled Staples to simplify its catalog management using SQL++ and JSON, but also improved database performance and reliability.
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Compare Capella database services
Compare Couchbase Capella™ with other cloud Database-as-a-Service providers like MongoDB’s™ Atlas cloud service and Amazon’s DynamoDB database service. Find out why Couchbase Capella is the best solution for you.