Migrate From MongoDB to InfluxDB Seamlessly
If you are using MongoDB for time series data, migrating to InfluxDB can improve performance, reduce complexity, and lower your storage costs.
Why look at a proposed build time series database?
Time series databases are purpose-built to handle the high-volume, high-frequency nature of timestamped data with optimized storage compression, fast ingestion rates, and time-based queries that would be slow and inefficient in general-purpose databases not designed for continuous streams of temporal data
MongoDB, as a document-oriented database, lacks the columnar storage and time-based indexing optimizations needed for efficient time series aggregations and would struggle with the write-heavy workloads and temporal query patterns that time series applications demand.
Why do MongoDB customers migrate to InfluxDB?
“Can’t support high ingestion”
“Performance issues”
“Too expensive”
High-Performance Time Series Engine
Purpose-built for time series data, InfluxDB handles millions of data points per second with unlimited cardinality, capturing every detail without performance loss. Unlike general databases that struggle with high-frequency writes and time-based queries InfluxDB architecture is optimized for it.
Cost-Efficient Storage
Reduce storage costs by up to 90% with InfluxDB's compression and object storage vs. general databases like MongoDB that create expensive overhead. InfluxDB's purpose-built architecture manages data affordably with easy access and high availability.
Open Standards and Ecosystem Integration
Query with standard SQL, connect to BI tools, or feed ML pipelines—all using open formats like Apache Arrow and Parquet. No vendor lock-in, just seamless integration with your existing stack
Flexible Deployment Options
Deploy anywhere: fully managed cloud, self-hosted infrastructure, or edge devices. From single-node installs that start in seconds to enterprise clusters with high availability and read replicas.
Explore your migration options
Purpose-built database for all types of time series data at any scale. Deploy easily, anywhere. Start for free.
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| Enterprise-grade scalability | — | Supports unlimited cardinality and horizontal scaling, accommodating enterprise-scale deployments effortlessly | Supports unlimited cardinality and horizontal scaling, accommodating enterprise-scale deployments effortlessly |
| Writes | 5MB/5 mins (free) / 300MB/5 mins (paid) | Limitless | Limitless |
| Queries (data read) | 300MB/5 mins | No applied service quota | No applied service quota |
| STORAGE | |||
| Type | Pay for what you use | Self-managed storage, S3-compatible object store | Low-cost storage, starts at 1 TB |
| Storage and query performance optimization | Within service limits | |
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| Data retention | 30 days (free) / Unlimited (paid) | Limitless | Limitless |
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| Read replica | — | |
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| Disaster recovery support | — | Not applicable | |
| Private networking | — | Not applicable | Available as an add-on |
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| GETTING STARTED | |||
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Migration made simple
Migrating from MongoDB to InfluxDB is easy. Here’s a step-by-step guide to ensure a smooth transition of your existing workload.
Choose your InfluxDB 3 deployment
InfluxDB 3 is designed to support time series data at any scale. There are several versions you can choose from depending on your workload.
- InfluxDB Cloud Serverless - For growing workloads, it offers multi-tenancy, elastic scaling, SQL support, and usage-based pricing.
- InfluxDB 3 Enterprise - If you need high scalability and availability on-premise, InfluxDB 3 Enterprise allows for multi-node deployments that can allow for independent scaling of query, write, and storage capacity.
Export your data from MongoDB
Once you’ve chosen which version of InfluxDB you are going to use, you will need to get your data out of MongoDB. To do this, you can use the mongoexport tool or create a custom script to extract your data into a JSON or CSV file. Your data must have a timestamp attached to be compatible with InfluxDB. If your data does not have a timestamp, one will be created at the time you write the data to InfluxDB. You may need to denormalize or flatten your data if you are using nested structures.
Transform your schema to fit InfluxDB
The InfluxDB 3 data model consists of tables that contain tags, fields, and a timestamp. You can map your MongoDB fields in the following way:
- table - collection
- tags - indexed fields. like device ID or city name
- fields - numeric or string values
- timestamp - Unix timestamps or MongoDB ISODate (InfluxDB supports up to nanosecond precision)
Write your data to InfluxDB
Once you have your exported data, you can write it to InfluxDB using Telegraf, the InfluxDB 3 client libraries, or the InfluxDB CLI. If you are working with a large amount of data, be sure to read the best practices on schema design and optimizing write performance.
Validate and explore your data
Explore your data using SQL, InfluxQL, or other tools like Grafana, InfluxDB Explorer, or Python to validate your schema and confirm your data migrated as expected.
Help getting started
Our team is ready to support your migration. Whether you're transitioning from MongoDB Atlas or a self-hosted instance, we’ll help you determine the best path forward and guide you through schema conversion, ingestion pipelines, and performance tuning.
Developers choose InfluxDB
The fastest time to awesome yet. Open source InfluxDB and Telegraf speed ingest, query in real-time, and easily scale
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Time series database
Source: DB Engines
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Contributors
InfluxDB is a G2 leader in time series
“InfluxDB is a strong database built specifically for time series data. It has made working with such data seamless and easy.”
— Verified G2 reviewer
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Easily install for Linux, Mac, RHEL, Docker:
curl -O https://www.influxdata.com/d/install_influxdb3.sh && sh install_influxdb3.sh enterprise
For Windows installation, see the Getting Started Guide.
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