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
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.
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.
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.
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.
Native time series collections
Quickly get started with a flexible schema optimized for high storage efficiency.
Low latency queries
Scale queries with automatic clustered indexes on time and secondary indexes on any metadata field.
Uncover patterns with window functions and calculate moving averages and sums over flexible time windows.
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.