MONGODB ATLAS

Performance

MongoDB Atlas makes it easy to scale your databases in any direction. Get more out of your existing resources with performance optimization tools and real-time visibility into database metrics.

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Scale On-Demand

With MongoDB Atlas, you can scale your databases up, down, or out in a few clicks or API calls.

Elastic Scalability

Adjust the instance size, memory, or storage capacity of your clusters with no application downtime. Provision and pay for the resources you need, when you need them.

Native Sharding

Scale horizontally across multiple machines with Atlas’s native sharding capabilities. Choose the number of shards and sharding strategy that meets your needs.

Capacity Auto-Scaling

Enable fully automated capacity management and have Atlas adjust database storage and sizes as needed by tracking resource utilization metrics in real-time.

We could see that using a horizontally scalable document database was a perfect fit for player-account based games. The ability to create a high traffic volume, highly scalable solution is about knowing the tiny details. To do that, normally engineers need to focus on many different parts of the stack but MongoDB Atlas and MongoDB’s support gives us a considerable shortcut.

Yordan Gyurchev, Technical Director, SEGA

We run our application on a deployment using the M30 size instances with the auto-expanding storage option enabled. When our disk utilization approaches 90%, Atlas automatically provisions us more with no impact to availability. And if we experience spikes in traffic like we have in the past, we can easily scale up or out using MongoDB Atlas by either clicking a few buttons in the UI or triggering a scaling event using the API.

Ken Hoff, Developer Advocate, Stream

We could see that using a horizontally scalable document database was a perfect fit for player-account based games. The ability to create a high traffic volume, highly scalable solution is about knowing the tiny details. To do that, normally engineers need to focus on many different parts of the stack but MongoDB Atlas and MongoDB’s support gives us a considerable shortcut.

Yordan Gyurchev, Technical Director, SEGA

We run our application on a deployment using the M30 size instances with the auto-expanding storage option enabled. When our disk utilization approaches 90%, Atlas automatically provisions us more with no impact to availability. And if we experience spikes in traffic like we have in the past, we can easily scale up or out using MongoDB Atlas by either clicking a few buttons in the UI or triggering a scaling event using the API.

Ken Hoff, Developer Advocate, Stream

Over time, we realized that what we had originally provisioned was may more than what we needed. And at that point, we could have either reprovisioned a cluster to again manage ourselves or just migrate our data to MongoDB Atlas and never have to worry about this problem ever again.

Gavin Cooper, Senior Director of Product and Engineering, Surfline

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Optimize Resource Efficiency

MongoDB Atlas helps you improve database performance with intelligent index and schema suggestions, automatic data tiering, and workload isolation for analytical queries.

Index Suggestions

The Performance Advisor in MongoDB Atlas automatically analyzes collections experiencing poor performance and recommends indexes to add. See examples of slow-running queries with relevant metrics and create suggested indexes in a few clicks.

Schema Suggestions

The Performance Advisor also provides actionable schema advice for your slowest and most active collections. Each recommendation offers context and evidence so you can review potential data model inefficiencies that are impacting your database performance.

Online Archive (Beta)

With Online Archive, you can tier your data across fully managed databases and cloud object storage and query it through a single endpoint. Automatically archive historical data and save on operational and transactional data storage costs without compromising on query performance.

Workload Isolation

Configure read-only secondary nodes to run analytical workloads, such as MongoDB Charts or the BI Connector. This ensures your operational workloads are not impacted by resource-intensive queries on the same database.

The Performance Advisor has made indexing the database and optimizing queries a no-brainer.

Nicolae Gudumac, CTO & Co-founder, Planable

The Performance Advisor has been hugely valuable to the team–any unindexed queries are captured and alerted to us, so we can add a new index in minutes if we need to.

Jon Vines, Software Development Team Lead, AO.com

The Performance Advisor has made indexing the database and optimizing queries a no-brainer.

Nicolae Gudumac, CTO & Co-founder, Planable

The Performance Advisor has been hugely valuable to the team–any unindexed queries are captured and alerted to us, so we can add a new index in minutes if we need to.

Jon Vines, Software Development Team Lead, AO.com

Atlas’s Performance Advisor makes it easy to identify places for improvement and review how data has changed since the last time a database was indexed.

Sankaet Pathak, CEO, SynapseFI

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Full Performance Visibility

MongoDB Atlas takes the pain out of database monitoring and diagnostics with custom alerts, real-time performance tracking, and historical metrics.

Real-Time Performance Panel

See live performance metrics for dedicated clusters, including operations, disk usage, connections, IOPS, hottest collections, and slowest queries.

Custom Alerts

Receive notifications when database operations, server usage, or other conditions reach defined thresholds that affect your cluster’s performance. Get alerts over email, text, and channels you already use.

Key Database Metrics

Create dashboards from dozens of throughput, performance, and utilization metrics to analyze historical database performance down to one minute granularity.

The Query Profiler is a tool that visualizes slow-running operations and their key performance statistics in the MongoDB Atlas UI

Query Profiler

Diagnose issues quickly with the help of the Query Profiler, which surfaces long-running queries and their key performance statistics. Review historical operations to quickly identify outliers and query patterns across collections and operation types.

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