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Atlas

Time Series.
Build faster, gain insight, reduce cost.

Build and run time series applications of any scale for any industry with greater ease, speed, and economy than ever before.
View Documentation
Atlas architecture diagram highlighting "Transactional" and "Analytical" within the Unified Interface category.
MongoDB optimizes for the demands of time series workloads – streaming data ingestion, indexing, fast query processing, and compressed storage footprint. Your teams get time series apps to market faster, with less effort and at lower cost.
  • Time series collections, queries and analytics
  • Automated data lifecycle
An illustration of a phone connected to data and a web page to signify simple app development.

Simplify app development

Build apps for the unique performance and scale demands of time series data. Eliminate lengthy development cycles. Quickly bring new apps to market with native time series collections that automatically optimize your schema for high storage efficiency, low latency queries, and real time analytics.
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Surface insights and anticipate outcomes

Collect data at the edge and process, query, and aggregate it in place with a single, unified Query API. Scale and gain faster insights with automatic indexing, rich window functions, and data densification.
An illustration of shapes and data charts going into a green box to represent seamlessly managing data lifecycles.

Reduce complexity
and cost

Eliminate the time and the complexity of having to stitch together multiple technologies. Seamlessly and economically manage the entire time series data lifecycle in MongoDB – from ingestion, storage, querying, real-time analysis, and visualization through to online archiving as data ages.
Data charts, images, and papers with a magnifying glass clustered around 3 green tiers to represent simplified data esstates.

Simplify your data estate

Overcome legacy trade-offs. Eliminate specialized data stores that lead to more data silos, data movement, and operational overhead. Efficiently and securely blend time series and enterprise data within a single versatile, flexible database and use a single query API to power almost any workload.
Feature overview
mdb_time_series
Native time series collections
Quickly get started with a flexible schema optimized for high storage efficiency.
realm_fast_queries
Low latency queries
Scale queries with automatic clustered indexes on time and secondary indexes on any metadata field.
general_features_data_analytics
Real-time analytics
Uncover patterns with window functions and calculate moving averages and sums over flexible time windows.
general_features_management
Full data lifecycle management
Support the entire time series lifecycle from ingestion, storage, analysis, and visualization to online archiving as
data ages.

Get started with
time series

Eliminate lengthy development cycles and quickly build schemas, queries, and analytics tuned for the unique performance demands of time series workloads.
View Documentation
Time series collections
Hands-free optimized schema supporting high storage efficiency and low latency queries.
Read the docs
Window functions
Unlock insights faster with new Window Functions and Temporal Operators.
Learn about the MongoDB Query API
Data densification
Handle missing data with ease.
View aggregation pipeline operators
Time series collections
Hands-free optimized schema supporting high storage efficiency and low latency queries.
Read the docs
JSON
Window functions
Unlock insights faster with new Window Functions and Temporal Operators.
Learn about the MongoDB Query API
JSON
Data densification
Handle missing data with ease.
View aggregation pipeline operators
JSON
JSON

Get started with MongoDB Time Series

Find out how to leverage time series data to create great
app experiences.
An illustration of a laptop with information bars hovering over it to represent the time series collections.
MongoDB time series collections
Learn more about the new time series collections and how you can start building time series
applications today.
Learn More
An illustration of a file folder with papers and a phone to represent MongoDB 5.1.
MongoDB 5.1: What’s new
Check out all the new features in MongoDB 5.0 and 5.1
Download Now
An illustration of blue data points on a graph to represent analysis with the time series collections.
Currency analysis with time series collections
Read the three-part blog on how to build a currency analysis platform with MongoDB
time series
Learn more
An image of the Kafka Connector logo.
New version of the Kafka Connector
Our Kafka Connector now supports time series
Learn more

Get the most out of Atlas

Build and run applications like IoT and financial analytics with MongoDB native time series capabilities.
atlas_online_archive
Online Archive
Automatically tier aged data out of the database and into cloud object storage without losing access to it or dealing with ETL pipelines.
Learn more
atlas_data_lake
Data Lake
Seamlessly and economically manage your entire data lifecycle.
Learn more
atlas_charts
Charts
Create graphs from any Atlas times series collection and embed visualizations into your applications for a rich user experience.
Learn more

Build time series applications on MongoDB Atlas

Natively support the entire time series data lifecycle – from ingestion, storage, querying, real-time analysis, and visualization to online archiving.
Try Free
MONGODB NATIVE TIME SERIES
  • Time series collections
  • Clustered indexes
  • Time series queries & analytics
  • Automated data lifecycle
  • Integrate with enterprise data