Choosing 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 Graphite and PostgreSQL so you can quickly see how they compare against each other.

The primary purpose of this article is to compare how Graphite and PostgreSQL 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.

Graphite vs PostgreSQL Breakdown


 
Database Model

Time series database

Relational database

Architecture

Graphite can be deployed on-premises or in the cloud, and it supports horizontal scaling by partitioning data across multiple backend nodes.

PostgreSQL can be deployed on various platforms, such as on-premises, in virtual machines, or as a managed cloud service like Amazon RDS, Google Cloud SQL, or Azure Database for PostgreSQL.

License

Apache 2.0

PostgreSQL license (similar to MIT or BSD)

Use Cases

Monitoring, observability, IoT, real-time analytics, DevOps, application performance monitoring

Web applications, geospatial data, business intelligence, analytics, content management systems, financial applications, scientific applications

Scalability

Horizontally scalable, supports clustering and replication for high availability and performance

Supports vertical scaling, horizontal scaling through partitioning, sharding, and replication using available tools

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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.

PostgreSQL Overview

PostgreSQL, also known as Postgres, is an open-source relational database management system that was first released in 1996. It has a long history of being a robust, reliable, and feature-rich database system, widely used in various industries and applications. PostgreSQL is known for its adherence to the SQL standard and extensibility, which allows users to define their own data types, operators, and functions. It is developed and maintained by a dedicated community of contributors and is available on multiple platforms, including Windows, Linux, and macOS.


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.

PostgreSQL for Time Series Data

PostgreSQL can be used for time series data storage and analysis, although it was not specifically designed for this use case. With its rich set of data types, indexing options, and window function support, PostgreSQL can handle time series data. However, Postgres will not be as optimized for time series data as specialized time series databases when it comes to things like data compression, write throughput, and query speed. PostgreSQL also lacks a number of features that are useful for working with time series data like downsampling, retention policies, and custom SQL functions for time series data analysis.


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.

PostgreSQL Key Concepts

  • MVCC: Multi-Version Concurrency Control is a technique used by PostgreSQL to allow multiple transactions to be executed concurrently without conflicts or locking.
  • WAL: Write-Ahead Logging is a method used to ensure data durability by logging changes to a journal before they are written to the main data files.
  • TOAST: The Oversized-Attribute Storage Technique is a mechanism for storing large data values in a separate table to reduce the main table’s disk space consumption.


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.

PostgreSQL Architecture

PostgreSQL is a client-server relational database system that uses the SQL language for querying and manipulation. It employs a process-based architecture, with each connection to the database being handled by a separate server process. This architecture provides isolation between different users and sessions. PostgreSQL supports ACID transactions and uses a combination of MVCC, WAL, and other techniques to ensure data consistency, durability, and performance. It also supports various extensions and external modules to enhance its functionality.

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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.

PostgreSQL Features

Extensibility

PostgreSQL allows users to define custom data types, operators, and functions, making it highly adaptable to specific application requirements.

PostgreSQL has built-in support for full-text search, enabling users to perform complex text-based queries and analyses.

Geospatial support

With the PostGIS extension, PostgreSQL can store and manipulate geospatial data, making it suitable for GIS applications.


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.

PostgreSQL Use Cases

Enterprise applications

PostgreSQL is a popular choice for large-scale enterprise applications due to its reliability, performance, and feature set.

GIS applications

With the PostGIS extension, PostgreSQL can be used for storing and analyzing geospatial data in applications like mapping, routing, and geocoding.

OLTP workloads

As a relational database, PostgreSQL is a good fit for pretty much any application that involves transactional workloads.


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.

PostgreSQL Pricing Model

PostgreSQL is open source software, and there are no licensing fees associated with its use. However, costs can arise from hardware, hosting, and operational expenses when deploying a self-managed PostgreSQL server. Several cloud-based managed PostgreSQL services, such as Amazon RDS, Google Cloud SQL, and Azure Database for PostgreSQL, offer different pricing models based on factors like storage, computing resources, and support.