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

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

Snowflake vs OpenTSDB Breakdown


 
Database Model

Cloud data warehouse

Time series database

Architecture

Snowflake can be deployed across multiple cloud providers, including AWS, Azure, and Google Cloud

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

License

Closed source

GNU LGPLv2.1

Use Cases

Big data analytics, Data warehousing, Data engineering, Data sharing, Machine learning

Monitoring, observability, IoT, log data storage

Scalability

Highly scalable with multi-cluster shared data architecture, automatic scaling, and performance isolation

Horizontally scalable across multiple nodes using HBase as its storage backend

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Snowflake Overview

Snowflake is a cloud-based data warehousing platform that was founded in 2012 and officially launched in 2014. It is designed to enable organizations to efficiently store, process, and analyze large volumes of structured and semi-structured data. Snowflake’s unique architecture separates storage, compute, and cloud services, allowing users to independently scale and optimize each component.

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.


Snowflake for Time Series Data

While Snowflake is not specifically designed for time series data, it can still effectively store, process, and analyze such data due to its scalable and flexible architecture. Snowflake’s columnar storage format, combined with its powerful query engine and support for SQL, makes it a suitable option for time series data analysis.

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.


Snowflake Key Concepts

  • Virtual Warehouse: A compute resource in Snowflake that processes queries and performs data loading and unloading. Virtual Warehouses can be independently scaled up or down based on demand.
  • Micro-Partition: A storage unit in Snowflake that contains a subset of the data in a table. Micro-partitions are automatically optimized for efficient querying.
  • Time Travel: A feature in Snowflake that allows users to query historical data at specific points in time or within a specific time range.
  • Data Sharing: The ability to securely share data between Snowflake accounts, without the need to copy or transfer the 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.


Snowflake Architecture

Snowflake’s architecture separates storage, compute, and cloud services, allowing users to scale and optimize each component independently. The platform uses a columnar storage format and supports ANSI SQL for querying and data manipulation. Snowflake is built on top of AWS, Azure, and GCP, providing a fully managed, elastic, and secure data warehouse solution. Key components of the Snowflake architecture include databases, tables, virtual warehouses, and micro-partitions.

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.

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Snowflake Features

Elasticity

Snowflake’s architecture allows for independent scaling of storage and compute resources, enabling users to quickly adjust to changing workloads and demands.

Fully Managed

Snowflake is a fully managed service, eliminating the need for users to manage infrastructure, software updates, or backups.

Security

Snowflake provides comprehensive security features, including encryption at rest and in transit, multi-factor authentication, and fine-grained access control.

Data Sharing

Snowflake enables secure data sharing between accounts without the need to copy or transfer data.

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.


Snowflake Use Cases

Data Warehousing

Snowflake provides a scalable, secure, and fully managed data warehousing solution, making it suitable for organizations that need to store, process, and analyze large volumes of structured and semi-structured data.

Data Lake

Snowflake can serve as a data lake for ingesting and storing large volumes of raw, unprocessed data, which can be later transformed and analyzed as needed.

Data Integration and ETL

Snowflake’s support for SQL and various data loading and unloading options makes it a good choice for data integration and ETL

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.


Snowflake Pricing Model

Snowflake offers a pay-as-you-go pricing model, with separate charges for storage and compute resources. Storage is billed on a per-terabyte, per-month basis, while compute resources are billed based on usage, measured in Snowflake Credits. Snowflake offers various editions, including Standard, Enterprise, Business Critical, and Virtual Private Snowflake, each with different features and pricing options. Users can also opt for on-demand or pre-purchased, discounted Snowflake Credits.

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.