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 OpenTSDB and VictoriaMetrics so you can quickly see how they compare against each other.

The primary purpose of this article is to compare how OpenTSDB and VictoriaMetrics 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.

OpenTSDB vs VictoriaMetrics Breakdown


 
Database Model

Time series database

Time series database

Architecture

OpenTSDB can be deployed on-premises or in the cloud, with HBase running on a distributed cluster of nodes.

VictoriaMetrics can be deployed as a single-node instance for small-scale applications or as a clustered setup for large-scale applications, offering horizontal scalability and replication.

License

GNU LGPLv2.1

Apache 2.0

Use Cases

Monitoring, observability, IoT, log data storage

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

Scalability

Horizontally scalable across multiple nodes using HBase as its storage backend

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

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OpenTSDB Overview

OpenTSDB (Open Time Series Database) is an open-source, distributed, and scalable time series database built on top of Apache HBase, a NoSQL database. OpenTSDB was designed to address the growing need for storing and processing large volumes of time series data generated by various sources, such as IoT devices, sensors, and monitoring systems. It was initially developed by StumbleUpon in 2010 and later became an independent project with an active community of contributors.

VictoriaMetrics Overview

VictoriaMetrics is an open source time series database developed by the company VictoriaMetrics. The database aims to assist individuals and organizations in addressing their big data challenges by providing state-of-the-art monitoring and observability solutions. VictoriaMetrics is designed to be a fast, cost-effective, and scalable monitoring solution and time series database.


OpenTSDB for Time Series Data

OpenTSDB is designed for time series data storage and analysis, making it an ideal choice for managing large scale time series datasets. Its architecture enables high write and query performance, and it can handle millions of data points per second with minimal resource consumption. OpenTSDB’s flexible querying capabilities allow users to perform complex analysis on time series data efficiently.

VictoriaMetrics for Time Series Data

VictoriaMetrics is designed for time series data, making it a solid choice for applications that involve the storage and analysis of time-stamped data. It provides high-performance storage and retrieval capabilities, enabling efficient handling of large volumes of time series data.


OpenTSDB Key Concepts

  • Data Point: A single measurement in time consisting of a timestamp, metric, value, and associated tags.
  • Metric: A named value that represents a specific aspect of a system, such as CPU usage or temperature.
  • Tags: Key-value pairs associated with data points that provide metadata and help categorize and query the data.

VictoriaMetrics Key Concepts

  • Time Series: VictoriaMetrics stores data in the form of time series, which are sequences of data points indexed by time.
  • Metric: A metric represents a specific measurement or observation that is tracked over time.
  • Tag: Tags are key-value pairs associated with a time series and are used for filtering and grouping data.
  • Field: Fields contain the actual data values associated with a time series.
  • Query Language: VictoriaMetrics supports its own query language, which allows users to retrieve and analyze time series data based on specific criteria.


OpenTSDB Architecture

OpenTSDB is built on top of Apache HBase, a distributed and scalable NoSQL database, and relies on its architecture for data storage and management. OpenTSDB stores time series data in HBase tables, with data points organized by metric, timestamp, and tags. The database uses a schema-less data model, which allows for flexibility when adding new metrics and tags. The OpenTSDB architecture also supports horizontal scaling by distributing data across multiple HBase nodes.

VictoriaMetrics Architecture

VictoriaMetrics is available in two forms: Single-server-VictoriaMetrics and VictoriaMetrics Cluster. The Single-server-VictoriaMetrics is an all-in-one binary that is easy to use and maintain. It vertically scales well and can handle millions of metrics per second. On the other hand, VictoriaMetrics Cluster consists of components that allow for building horizontally scalable clusters, enabling high availability and scalability in demanding environments. The architecture of VictoriaMetrics enables users to choose the deployment option that best suits their needs and scale their database infrastructure as required.

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OpenTSDB Features

Scalability

OpenTSDB’s distributed architecture allows for horizontal scaling, ensuring that the database can handle growing volumes of time series data.

Data Compression

OpenTSDB uses various compression techniques to reduce the storage footprint of time series data.

Query Language with time series support

OpenTSDB features a flexible query language that supports aggregation, downsampling, filtering, and other operations for analyzing time series data.

VictoriaMetrics Features

High performance

VictoriaMetrics is optimized for high-performance storage and retrieval of time series data. It can efficiently handle millions of metrics per second and offers fast query execution for real-time analysis.

Scalability

The architecture of VictoriaMetrics allows for both vertical and horizontal scalability, enabling users to scale their monitoring and time series database infrastructure as their data volume and demand grow.

Cost-effectiveness

VictoriaMetrics provides a cost-effective solution for managing time series data. Its efficient storage and query capabilities contribute to minimizing operational costs while maintaining high performance.


OpenTSDB Use Cases

Monitoring and Alerting

OpenTSDB is well-suited for large-scale monitoring and alerting systems that generate vast amounts of time series data from various sources.

IoT Data Storage

OpenTSDB can store and analyze time series data generated by IoT devices, such as sensors and smart appliances, enabling real-time insights and analytics.

Performance Analysis

OpenTSDB’s flexible querying capabilities make it an ideal choice for analyzing system and application performance metrics over time.

VictoriaMetrics Use Cases

Monitoring and Observability

VictoriaMetrics is widely used for monitoring and observability purposes, allowing organizations to collect, store, and analyze metrics and performance data from various systems and applications. It provides the necessary tools and capabilities to track and visualize key performance indicators, troubleshoot issues, and gain insights into system behavior.

IoT Data Management

VictoriaMetrics is suitable for handling large volumes of time series data generated by IoT devices. It can efficiently store and process sensor data, enabling real-time monitoring and analysis of IoT ecosystems. VictoriaMetrics allows for tracking and analyzing data from factories, manufacturing plants, satellites, and other IoT devices.

Capacity Planning

VictoriaMetrics enables retrospective analysis and forecasting of metrics for capacity planning purposes. It allows organizations to analyze historical data, identify patterns and trends, and make informed decisions about resource allocation and future capacity requirements.


OpenTSDB Pricing Model

OpenTSDB is open-source software, which means it is free to use without any licensing fees. However, the cost of running OpenTSDB depends on the infrastructure required to support the underlying HBase database, such as cloud services or on-premises hardware.

VictoriaMetrics Pricing Model

VictoriaMetrics is an open source project, which means it is available for free usage and doesn’t require any licensing fees. Users can download the binary releases, Docker images, or source code to set up and deploy VictoriaMetrics without incurring any direct costs. VictoriaMetrics also has paid offerings for on-prem Enterprise products and managed VictoriaMetrics instances.