InfluxDB vs Graphite
A detailed comparison
Compare InfluxDB and Graphite for time series and OLAP workloads
Updated June 12, 2026
Learn About Time Series DatabasesChoosing the right database is a critical choice when building any software application. All databases have different strengths and weaknesses when it comes to performance, so deciding which database has the most benefits and the most minor downsides for your specific use case and data model is an important decision. Below you will find an overview of the key concepts, architecture, features, use cases, and pricing models of InfluxDB and Graphite so you can quickly see how they compare against each other.
The primary purpose of this article is to compare how InfluxDB and Graphite perform for workloads involving time series data, not for all possible use cases. Time series data typically presents a unique challenge in terms of database performance. This is due to the high volume of data being written and the query patterns to access that data. This article doesn't intend to make the case for which database is better; it simply provides an overview of each database so you can make an informed decision.
InfluxDB vs Graphite Breakdown
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| Database Model | Time series database |
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| Architecture | Cloud-native architecture available as a fully managed cloud service or self-managed on your own hardware |
Graphite can be deployed on-premises or in the cloud, and it supports horizontal scaling by partitioning data across multiple backend nodes. |
| License | InfluxDB 3 Core: MIT (open source). InfluxDB 3 Enterprise: commercial license. |
Apache 2.0 |
| Use Cases | Monitoring, observability, IoT, real-time analytics, Industrial AI, Aerospace |
Monitoring, observability, IoT, real-time analytics, DevOps, application performance monitoring |
| Scalability | Horizontally scalable with decoupled compute and storage; object storage reduces infrastructure costs significantly |
Horizontally scalable, supports clustering and replication for high availability and performance |
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Whether you are looking for cost savings, lower management overhead, or open source, InfluxDB can help.
InfluxDB Overview
InfluxDB is a time series database built for storing metrics, events, logs, and traces. InfluxData released the first version in 2013. It is the most widely deployed time series database in the world and consistently ranks #1 in the DB-Engines time series database category with a 21.60 score.
InfluxDB 3 is the most recent version of InfluxDB. Its architecture separates compute and storage, so each scales independently based on workload demands. InfluxDB 3 supports standard SQL and InfluxQL, a time-series-optimized query language with built-in functions for downsampling, windowed aggregations, and time-range filtering.
InfluxDB 3 is available in five deployment options:
- InfluxDB 3 Core: Open source, self-managed, MIT licensed.
- InfluxDB 3 Enterprise: Self-managed with enterprise capabilities including clustering, role-based access control, and automated backup and restore.
- InfluxDB Cloud Serverless: Fully managed, usage-based pricing, available across major cloud providers.
- InfluxDB Cloud Dedicated: Managed cloud on dedicated infrastructure for workloads requiring isolation or hardware-level configuration.
- Amazon Timestream for InfluxDB: InfluxDB fully managed by AWS, natively integrated
Graphite Overview
Graphite is an open-source monitoring and graphing tool created in 2006 by Orbitz and open sourced in 2008. Graphite is designed for storing time series data and is widely used for collecting, storing, and visualizing metrics from various sources, such as application performance, system monitoring, and business analytics.
InfluxDB for Time Series Data
InfluxDB is the right choice when the workload is time series by nature: data arrives continuously, records are rarely modified after they are written, queries span time ranges, and volume grows with the number of sources rather than user activity.
InfluxDB is purpose-built for these workloads:
- Infrastructure and application observability: server metrics, container telemetry, Kubernetes monitoring
- Machine learning and AI: High-frequency feature data, model performance metrics, and inference telemetry at the latency and scale ML pipelines require
- IoT and industrial sensor data: high-frequency writes from large device fleets
- Energy systems: smart meters, battery storage telemetry, renewable asset monitoring
- Network telemetry: gNMI streaming, SNMP at scale, NetFlow records
- Satellite and aerospace: High-frequency telemetry from satellites, launch vehicles, and ground systems where data volume is extreme and decisions are time-sensitive
- Financial time series: tick data, price feeds, OHLCV aggregations
At high data volumes, InfluxDB’s columnar storage and object storage backend compress time series data aggressively and store it at a fraction of the cost of in-memory or block storage.
Graphite for Time Series Data
Graphite is specifically designed and optimized for time series data. It uses the Whisper database format, which efficiently stores and manages time series data by automatically aggregating and expiring data based on user-defined retention policies. Graphite supports a wide range of functions for querying, transforming, and aggregating time series data, enabling users to create custom graphs and dashboards. However, as Graphite focuses exclusively on time series data, it may not be suitable for other types of data or use cases that require more advanced data modeling or querying capabilities.
InfluxDB Key Concepts
Columnar storage: InfluxDB stores data in a column-oriented format using both open source and proprietary standards for persistent storage and Apache Arrow as the in-memory representation. Columnar storage produces strong compression ratios and fast time-range reads.
Data model: InfluxDB organizes data into databases, measurements (equivalent to tables), tags (indexed identifiers used for filtering), and fields (the measured values). InfluxDB 3 supports unlimited tables and columns. Data models evolve without schema migrations or predefined column limits.
Query languages: InfluxDB supports standard SQL and InfluxQL. InfluxQL includes built-in time-series functions: gap filling, window aggregations, downsampling, and rate calculations from counter data.
Decoupled architecture: InfluxDB 3 separates ingestion, query compute, and storage into independently scalable components. Teams tune each layer to workload requirements rather than provisioning for peak across all three simultaneously.
Retention policies: Users configure retention policies that automatically expire data after a defined duration. No manual partition drops, retention scripts, or index rebuilds required.
Telegraf integration: Telegraf, InfluxData’s open-source data collection agent, connects to 400+ data sources out of the box and writes directly to InfluxDB. It is part of the standard telemetry collection stack for tens of thousands of teams worldwide.
Unlimited Cardinality: The InfluxDB 3 storage engine enables high-performance queries across tables with millions of columns without impacting query performance.
Graphite Key Concepts
- Metric: A metric in Graphite represents a time series data point, consisting of a path (name), timestamp, and value.
- Series: A series is a collection of metrics that are all related to the same thing. For example, you might have a series for CPU usage, a series for memory usage, and a series for disk usage.
- Whisper: Whisper is a fixed-size, file-based time series database format used by Graphite. It automatically manages data retention and aggregation.
- Carbon: Carbon is the daemon responsible for receiving, caching, and storing metrics in Graphite. It listens for incoming metrics and writes them to Whisper files.
- Graphite-web: Graphite-web is the web application that provides a user interface for visualizing and querying the stored time series data.
InfluxDB Architecture
InfluxDB 3 separates data ingestion, querying, compaction, and garbage collection into components that operate independently. This separation allows compute and storage to scale in different directions based on actual workload requirements.
Data written to InfluxDB flows through ingesters with millisecond-level latency and is immediately queryable. A background compactor consolidates new files and moves them to object storage. The query layer pulls seamlessly from both in-flight ingester data and object storage, so there is no gap between data arrival and query availability.
Object storage handles long-term persistence at low cost. Teams retain data at higher frequencies and for longer periods without driving up infrastructure costs on expensive storage tiers.
Graphite Architecture
Graphite’s architecture consists of several components, including Carbon, Whisper, and Graphite-web. Carbon is responsible for receiving metrics from various sources, caching them in memory, and storing them in Whisper files. Whisper is a file-based time series database format that efficiently manages data retention and aggregation. Graphite-web is the web application that provides a user interface for querying and visualizing the stored time series data. Graphite can be deployed on a single server or distributed across multiple servers for improved performance and scalability.
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InfluxDB Features
High-performance storage and querying
InfluxDB 3 is optimized for time series at every layer: ingestion, storage, and query execution. InfluxDB 3.10 delivers significantly faster query performance compared to prior InfluxDB 3 releases, with the most pronounced gains on single-series lookups, real-time telemetry queries, and metadata operations. Performance varies by workload.
Retention policies
InfluxDB automatically expires data after a configured duration. No external orchestration required.
Data compression
InfluxDB 3’s storage engine delivers strong compression ratios on time series data. Background compaction continuously consolidates smaller files into larger ones that are cheaper to store and faster to query.
Horizontal scaling and clustering
InfluxDB 3 Enterprise supports horizontal scaling and clustering, distributing data and query load across nodes for performance and fault tolerance.
Data tiering
InfluxDB 3 automatically moves data between hot and cold storage tiers. Recent data stays accessible for low-latency queries. Older data moves to object storage, where it remains queryable at lower cost without manual lifecycle management.
Row-level deletions
Users delete individual data points or subsets within a table without dropping entire tables or databases.
Auto-Distinct Value Caching
InfluxDB 3.10 automatically creates caches for metadata queries, making operations like SHOW TAG VALUES significantly faster without manual cache configuration.
Processing Engine
InfluxDB 3 runs Python code directly inside the database for real-time transformations, anomaly detection, and forecasting. Plugins trigger on a schedule, via HTTP requests, or on data write with no external processing layer required.
Graphite Features
Real-time monitoring and visualization
Graphite provides real-time monitoring and visualization capabilities, allowing users to track and analyze their time series data as it is collected.
Flexible querying and aggregation functions
Graphite supports a wide range of functions for querying, transforming, and aggregating time series data, enabling users to create custom graphs and dashboards tailored to their specific needs.
Data retention and aggregation
Graphite’s Whisper database format automatically manages data retention and aggregation, reducing storage requirements and improving query performance.
InfluxDB Use Cases
Monitoring and alerting
InfluxDB stores and processes time series data from infrastructure, applications, and devices at scale. Combined with visualization tools like Grafana, teams build real-time dashboards and threshold-based alerting without query latency degrading as data accumulates.
Machine learning and AI
InfluxDB stores the high-frequency feature data, model performance metrics, and inference telemetry that ML pipelines depend on. The built-in Processing Engine runs anomaly detection and forecasting models directly against live data without a separate compute layer.
IoT data storage and analysis
High write throughput and configurable retention policies make InfluxDB a fit for IoT deployments where sensors generate continuous data streams. Teams ingest at high frequency, retain what matters, and query across the full dataset with consistent performance.
Energy systems
InfluxDB manages telemetry from smart meters, grid infrastructure, battery storage systems, and renewable assets at the write rates and retention windows energy operators require. Cell-level monitoring, cross-site portfolio analytics, and long-horizon capacity planning all run on the same platform without architectural workarounds.
Real-time analytics
InfluxDB handles application performance monitoring, user behavior tracking, and financial data analysis in real time. SQL and InfluxQL support lets teams run complex aggregations and time-windowed queries without a dedicated analytics layer.
Infrastructure and application monitoring
InfluxDB handles the cardinality and write throughput that infrastructure monitoring generates at scale: millions of unique tag combinations across hosts, services, containers, and endpoints. Teams query recent and historical data spanning months or years without separate storage tiers or query engines.
Satellite & Aerospace
InfluxDB stores and analyzes high-frequency telemetry from satellites, launch vehicles, and ground systems where data volume is extreme and query latency affects operational decisions. Object storage tiering keeps years of mission data accessible without runaway infrastructure costs.
Industrial AI
InfluxDB ingests continuous signals from PLCs, SCADA systems, and industrial sensors at the frequencies predictive maintenance and process optimization models require. The Processing Engine runs detection and forecasting plugins in-database, reducing latency between sensor data and actionable output.
Data historian augmentation
InfluxDB extends legacy data historians by capturing the high-resolution, high-frequency process data that traditional historians compress, downsample, or age out. Open SQL and InfluxQL access frees that data from closed historian interfaces, while object storage tiering retains full-fidelity history at a fraction of the cost of expanding the existing system. Teams bridge plant-floor signals into modern analytics or ML pipelines and run Processing Engine plugins against live and archived data, modernizing without ripping out the historian they already depend on.
Graphite Use Cases
Application performance monitoring
Graphite is widely used for monitoring the performance of applications and services, helping developers and operations teams track key metrics, such as response times, error rates, and resource utilization. By visualizing these metrics in real-time, users can identify performance bottlenecks, detect issues, and optimize their applications for better performance and reliability.
Infrastructure and system monitoring
Graphite is also popular for monitoring the health and performance of servers, networks, and other infrastructure components. By collecting and analyzing metrics such as CPU usage, memory consumption, network latency, and disk I/O, IT administrators can ensure their infrastructure is running smoothly and proactively address potential issues before they impact system performance or availability.
Business analytics and metrics
In addition to technical monitoring, Graphite can be used for tracking and visualizing business-related metrics, such as user engagement, sales data, or marketing campaign performance. By visualizing and analyzing these metrics over time, business stakeholders can gain insights into trends, identify opportunities for growth, and make data-driven decisions to improve their operations.
InfluxDB Pricing Model
InfluxDB offers several pricing options, including a free open source version, a cloud-based offering, and an enterprise edition for on-premises deployment:
- InfluxDB 3 Core: Free, open source, self-managed. Provides core time series database functionality on the InfluxDB 3 architecture.
- InfluxDB Cloud Serverless: Fully managed, multi-tenant cloud., pay-as-you-go. No infrastructure to manage. Available across major cloud providers.
- InfluxDB Cloud Dedicated: Managed deployment on dedicated infrastructure for workloads requiring isolation or hardware-level configuration control.
- InfluxDB 3 Enterprise: Self-managed enterprise deployment with clustering, role-based access control, automated backup and restore, and production support.
Graphite Pricing Model
Graphite is an open-source project, and as such, it is freely available for users to download, install, and use without any licensing fees. However, users are responsible for setting up and maintaining their own Graphite infrastructure, which may involve costs related to server hardware, storage, and operational expenses. There are also several commercial products and services that build on top of or integrate with Graphite, offering additional features, support, or managed hosting options at varying price points.
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