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 Amazon Timestream for LiveAnalytics and MySQL so you can quickly see how they compare against each other.

The primary purpose of this article is to compare how Amazon Timestream for LiveAnalytics and MySQL 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.

Amazon Timestream for LiveAnalytics vs MySQL Breakdown


 
Database Model

Time series database

Relational database

Architecture

Timestream is a fully managed, serverless time series database service that is only available on AWS.

MySQL uses a client-server model with a multi-layered server design. It supports the SQL query language and offers various storage engines, such as InnoDB and MyISAM, for different use cases. MySQL can be deployed on-premises, in the cloud, or as a managed service.

License

Closed source

GNU General Public License v2 (for the open-source Community Edition)

Use Cases

IoT, DevOps, time series analytics

Web applications, e-commerce, data warehousing, content management systems, business applications

Scalability

Serverless and automatically scalable, handling ingestion, storage, and query workload without manual intervention

Supports vertical scaling by adding more resources to a single node; horizontal scaling can be achieved through replication, sharding, and third-party tools

Looking for the most efficient way to get started?

Whether you are looking for cost savings, lower management overhead, or open source, InfluxDB can help.

Amazon Timestream for LiveAnalytics Overview

Timestream for LiveAnalytics is a fully managed, serverless time series database service developed by AWS. Launched in 2020, Amazon Timestream for LiveAnalytics is designed specifically for handling time series data, making it an ideal choice for IoT, monitoring, and analytics applications that require high ingestion rates, efficient storage, and fast querying capabilities. As a part of the AWS ecosystem, Timestream for LiveAnalytics easily integrates with other AWS services, simplifying the process of building and deploying time series applications in the cloud. AWS also offers Timestream for InfluxDB which is a managed version of InfluxDB that is compatible with InfluxDB 2.x APIs and released in partnership with InfluxData.

MySQL Overview

MySQL is an open source relational database management system that was first released in 1995. It is one of the most popular databases worldwide due to its ease of use, reliability, and performance. MySQL is widely used for web applications, online transaction processing, and data warehousing. Oracle Corporation acquired MySQL in 2010, but it remains open source software with an active community of contributors.


Amazon Timestream for LiveAnalytics for Time Series Data

Amazon Timestream for LiveAnalytics is designed specifically for handling time series data, making it a suitable choice for a wide range of applications that require high ingestion rates and efficient storage. Its dual-tiered storage architecture, consisting of the memory Store and magnetic Store, allows users to manage data retention and optimize storage costs based on data age and access patterns. Additionally, Timestream supports SQL-like querying and integrates with popular analytics tools, making it easy for users to gain insights from their time series data.

MySQL for Time Series Data

MySQL can be used for storing and analyzing time series data, but it will not be as efficient as a dedicated time series databases. MySQL’s flexibility and support for various indexing techniques can make it a suitable choice for small to medium sized time series datasets. For large-scale time series data workloads, with high write throughput or use cases where low latency queries are required, MySQL will tend to struggle unless highly customized.


Amazon Timestream for LiveAnalytics Key Concepts

  • Memory Store: In Amazon Timestream for LiveAnalytics, the Memory Store is a component that stores recent, mutable time series data in memory for fast querying and analysis.
  • Magnetic Store: The Magnetic Store in Amazon Timestream for LiveAnalytics is responsible for storing historical, immutable time series data on disk for cost-efficient, long-term storage.
  • Time-to-Live (TTL): Amazon Timestream for LiveAnalytics allows users to set a TTL on their time series data, which determines how long data is retained in the Memory Store before being moved to the Magnetic Store or deleted.

MySQL Key Concepts

  • Table: A collection of related data organized in rows and columns, which is the primary structure for storing data in MySQL.
  • Primary Key: A unique identifier for each row in a table, used to enforce data integrity and enable efficient querying.
  • Foreign Key: A column or set of columns in a table that refers to the primary key in another table, used to establish relationships between tables.


Amazon Timestream for LiveAnalytics Architecture

Amazon Timestream for LiveAnalytics is built on a serverless, distributed architecture that supports SQL-like querying capabilities. Its data model is specifically tailored for time series data, using time-stamped records and a flexible schema that can accommodate varying data granularities and dimensions. The core components of Timestream’s architecture include the Memory Store and the Magnetic Store, which together manage data retention, storage, and querying. The Memory Store is optimized for fast querying of recent data, while the Magnetic Store provides cost-efficient, long-term storage for historical data.

MySQL Architecture

MySQL is a relational database management system that uses SQL for defining and manipulating data. It follows the client-server model, where a MySQL server accepts connections from multiple clients and processes their queries. MySQL’s architecture includes a storage engine framework that allows users to choose from different storage engines, such as InnoDB, MyISAM, or Memory, to optimize the database for specific use cases.

Free Time-Series Database Guide

Get a comprehensive review of alternatives and critical requirements for selecting yours.

Amazon Timestream for LiveAnalytics Features

Serverless architecture

Amazon Timestream for LiveAnalytics serverless architecture eliminates the need for users to manage or provision infrastructure, making it easy to scale and reducing operational overhead.

Dual-tiered storage

Timestream’s dual-tiered storage architecture, consisting of the Memory Store and Magnetic Store, automatically manages data retention and optimizes storage costs based on data age and access patterns.

SQL-like querying

Amazon Timestream for LiveAnalytics supports SQL-like querying and integrates with popular analytics tools, making it easy for users to gain insights from their time series data.

Timestream for InfluxDB

For workloads that require near real-time queries with single millisecond latency AWS recommends using Timestream for InfluxDB rather than LiveAnalytics. Timestream for InfluxDB also provides compatibility with InfluxDB APIs for users who want an AWS managed service without having to update their code.

MySQL Features

ACID compliance

MySQL supports transactions and adheres to the ACID (Atomicity, Consistency, Isolation, Durability) properties, ensuring data integrity and consistency.

Scalability

MySQL can scale both vertically and horizontally, depending on the storage engine and configuration.

Replication and high availability

MySQL supports various replication techniques, including master-slave and master-master replication, to provide high availability and fault tolerance.


Amazon Timestream for LiveAnalytics Use Cases

IoT applications

Amazon Timestream for LiveAnalytic’s support for high ingestion rates and efficient storage makes it an ideal choice for monitoring and analyzing data from IoT devices, such as sensors and smart appliances.

Devops

LiveAnalytics can be used for general DevOps workloads like monitoring application health and utilization. For use cases that require real time monitoring with the lowest latency possible, AWS recommends using Timestream for InfluxDB.

Analytics

Amazon Timestream for LiveAnalytics can be used to track analytics data like web and application data. The built-in time series analytics functions can then be used to aggregate and analyze data to get valuable insights with increased developer productivity.

MySQL Use Cases

Web applications

MySQL is a popular choice for powering web applications, content management systems, and e-commerce platforms due to its flexibility, ease of use, and performance.

Online transaction processing (OLTP)

MySQL is suitable for OLTP systems that require high concurrency, fast response times, and support for transactions.

Data warehousing

While not specifically designed for data warehousing, MySQL can be used for small to medium-sized data warehouses, leveraging its support for indexing, partitioning, and other optimization techniques.


Amazon Timestream for LiveAnalytics Pricing Model

Amazon Timestream for LiveAnalytics offers a pay-as-you-go pricing model based on data ingestion, storage, and query execution. Ingestion costs are determined by the volume of data ingested into Timestream, while storage costs are based on the amount of data stored in the Memory Store and Magnetic Store. Query execution costs are calculated based on the amount of data scanned and processed during query execution. Timestream also offers a free tier for users to explore the service and build proof-of-concept applications without incurring costs.

MySQL Pricing Model

MySQL is available in multiple editions with different feature sets and pricing models. The MySQL Community Edition is open source and free to use, while the MySQL Enterprise Edition includes additional features, such as advanced security, monitoring, and management tools, and requires a subscription. Pricing for the Enterprise Edition depends on the number of server instances and the level of support required.