Amazon Timestream for LiveAnalytics vs MariaDB

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 MariaDB 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 MariaDB 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 Overview

Amazon Timestream for LiveAnalytics is a fully managed, serverless time series database service developed by Amazon Web Services (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 seamlessly integrates with other AWS services, simplifying the process of building and deploying time series applications in the cloud.

MariaDB Overview

MariaDB is an open-source relational database management system (RDBMS) that was created as a fork of MySQL in 2009 by the original developers of MySQL, led by Michael Widenius. The primary goal of MariaDB was to provide an open-source and community-driven alternative to MySQL, which was acquired by Oracle Corporation in 2008. MariaDB is compatible with MySQL and has enhanced features, better performance, and improved security. It is widely used by organizations worldwide and is supported by the MariaDB Foundation, which ensures its continued open-source development.

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, efficient storage, and fast querying capabilities. Its dual-tiered storage architecture, consisting of the Memory Store and Magnetic Store, allows Timestream to automatically 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.

MariaDB for Time Series Data

While MariaDB is not specifically designed for time series data, it can be used to store, process, and analyze time series data due to its flexible and extensible architecture. SQL support, along with analytics optimized storage engines like ColumnStore make it suitable for handling time series data at smaller levels of data volume.

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.

MariaDB Key Concepts

• Storage Engines: MariaDB supports multiple storage engines, each optimized for specific types of workloads or data storage requirements. Examples include InnoDB, MyISAM, Aria, and ColumnStore.
• Galera Cluster: A synchronous, multi-master replication solution for MariaDB that allows for high availability, fault tolerance, and load balancing.
• MaxScale: A database proxy for MariaDB that provides advanced features such as query routing, load balancing, and security.
• Connectors: MariaDB provides a variety of connectors to allow applications to interact with the database using various programming languages and APIs.

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.

MariaDB Architecture

MariaDB is a relational database that uses the SQL language for querying and data manipulation. Its architecture is based on a client-server model, with clients interacting with the server through various connectors and APIs. MariaDB supports multiple storage engines, allowing users to choose the most suitable engine for their specific use case. The database also offers replication and clustering options for high availability and load balancing.