Amazon Timestream
Serverless time-series database for IoT, metrics, and operational telemetry
InfluxDB
Real-time time series database for events and metrics
InfluxDB Core collects, processes, and stores time series data with sub-10ms query response times, SQL support, and object storage compatibility for monitoring and analytics workloads.
Overview
Purpose and Audience
InfluxDB Core is a time series database engineered for developers and operations teams who need real-time data ingest with fast query performance. It excels at building dashboards, monitoring systems, and automation solutions where millisecond-level response times matter.
Core Capabilities
The platform combines a diskless architecture with object storage support, delivering sub-10ms last-value queries and 30ms metadata queries. It provides SQL and InfluxQL query engines accessible via FlightSQL and HTTP APIs, plus an embedded Python VM for custom plugins and triggers. Data persists in Parquet format, enabling efficient storage and analytics integration.
Deployment and Compatibility
InfluxDB 3 Core maintains backward compatibility with InfluxDB 1.x and 2.x write APIs, simplifying migration paths. Deploy using Docker images, Debian/RPM packages, or tarballs. The architecture supports both cloud object storage and local disk with zero external dependencies, making it suitable for edge deployments, cloud environments, and on-premises infrastructure. Released under Apache-2.0 license.
Highlights
Sub-10ms last-value queries with diskless object storage architecture
SQL and InfluxQL query engines with FlightSQL and HTTP API support
Embedded Python VM for custom plugins, triggers, and data transformations
Backward compatible with InfluxDB 1.x and 2.x write APIs
Pros
- Exceptional query performance optimized for real-time dashboards and UIs
- Flexible storage options supporting object storage or local disk without dependencies
- Strong backward compatibility eases migration from earlier InfluxDB versions
- Parquet persistence enables integration with modern analytics toolchains
Considerations
- Relatively new GA release (April 2025) with evolving feature set
- Diskless architecture may require rethinking traditional database deployment patterns
- Limited track record compared to mature time series databases
- Python VM plugin system adds complexity for simple use cases
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Fit guide
Great for
- Real-time monitoring dashboards requiring sub-second query response times
- IoT sensor networks generating high-volume event streams
- Application performance monitoring with interactive user interfaces
- Teams migrating from InfluxDB 1.x or 2.x seeking performance improvements
Not ideal when
- Workloads requiring complex relational joins across multiple tables
- Projects needing long-term support guarantees on a mature release cycle
- Teams without infrastructure for object storage in diskless deployments
- Use cases where sub-second query performance is not a priority
How teams use it
Server Infrastructure Monitoring
Operations teams visualize CPU, memory, and disk metrics across thousands of servers with real-time dashboards updating every second.
Financial Trading Analytics
Trading platforms ingest market tick data and execute sub-10ms queries to power live price charts and algorithmic trading signals.
IoT Sensor Data Collection
Manufacturing facilities collect temperature, pressure, and vibration data from equipment sensors, triggering Python-based alerts when thresholds are exceeded.
Application Performance Monitoring
DevOps teams track request latency, error rates, and throughput across microservices, querying recent data to diagnose production incidents instantly.
Tech snapshot
Rust98%
Shell1%
HTML1%
Dockerfile1%
Python1%
Answer Set Programming1%
Frequently asked questions
What query performance can I expect from InfluxDB 3 Core?
Last-value queries return in under 10ms, while distinct metadata queries complete in approximately 30ms, making it suitable for real-time dashboards and interactive interfaces.
Is InfluxDB 3 Core compatible with previous versions?
Yes, it supports InfluxDB 1.x and 2.x write APIs and the InfluxDB 1.x query API (InfluxQL), enabling straightforward migration paths from earlier versions.
What storage options does the diskless architecture support?
InfluxDB 3 Core works with object storage services or local disk with no external dependencies, providing flexibility for cloud, on-premises, and edge deployments.
What query languages and APIs are available?
The database provides SQL and InfluxQL query engines accessible through FlightSQL and HTTP APIs, supporting both modern SQL tooling and legacy InfluxDB queries.
How does the embedded Python VM enhance functionality?
The Python VM enables custom plugins and triggers for data transformation, alerting logic, and workflow automation directly within the database without external processing.
Project at a glance
Active- Stars
- 31,125
- Watchers
- 31,125
- Forks
- 3,689
LicenseApache-2.0
Repo age12 years old
Last commit13 hours ago
Self-hostingSupported
Primary languageRust
Last synced 4 hours ago