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Amazon Athena VS Amazon Aurora

Compare Amazon Athena VS Amazon Aurora and see what are their differences

Amazon Athena logo Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

Amazon Aurora logo Amazon Aurora

MySQL and PostgreSQL-compatible relational database built for the cloud. Performance and availability of commercial-grade databases at 1/10th the cost.
  • Amazon Athena Landing page
    Landing page //
    2023-03-17
  • Amazon Aurora Landing page
    Landing page //
    2023-03-17

Amazon Athena features and specs

  • Serverless
    Athena is serverless, which means there's no need to set up or manage any infrastructure. You can start querying data immediately without worrying about managing underlying servers.
  • Pay-as-you-go
    You only pay for the queries you run, and the cost is based on the amount of data scanned by the queries. This is cost-effective, especially for infrequent querying.
  • Scalable
    Athena scales automatically, enabling it to handle large datasets and concurrent queries efficiently, without manual intervention.
  • Integration with AWS ecosystem
    Athena integrates seamlessly with other AWS services like S3, Glue, and QuickSight, making it easy to build comprehensive data pipelines and analytics solutions.
  • Supports standard SQL
    Athena uses standard SQL for querying, which makes it easy for users familiar with SQL to get started quickly.
  • Quick to deploy
    Since there is no infrastructure to manage, you can start querying your data within minutes of setting up Athena.
  • Supports a variety of data formats
    Athena supports multiple data formats including CSV, JSON, ORC, Avro, and Parquet, providing flexibility in data ingestion and storage.

Possible disadvantages of Amazon Athena

  • Cost of scanning large datasets
    While the pay-as-you-go model is beneficial, querying large datasets frequently can become expensive.
  • Performance
    For very complex queries or extremely large datasets, Athena's performance might not match that of a dedicated data warehouse solution.
  • Limited built-in visualization
    Athena does not provide built-in data visualization tools, so you'll need to integrate with other services like QuickSight or third-party tools for visual analytics.
  • Learning curve for optimal usage
    Even though Athena supports SQL, optimizing performance and cost efficiency might require a good understanding of how Athena processes data.
  • Data preparation
    Data might require preprocessing or organization in a specific way for optimal performance with Athena, which could add to the setup time and complexity.
  • Cold start latency
    Athena can experience latency during query initiation, known as cold start latency, which can be an issue for time-sensitive analytics.

Amazon Aurora features and specs

  • High Performance
    Amazon Aurora is designed to provide up to five times the throughput of standard MySQL and three times the throughput of standard PostgreSQL databases.
  • Scalability
    Aurora scales storage automatically, growing from 10GB up to 128TB with no downtime. This automatic scaling makes it ideal for applications with fluctuating workloads.
  • High Availability and Durability
    Aurora automatically replicates six copies of data across three availability zones and continuously backs up data to Amazon S3, ensuring durability.
  • Security
    Aurora offers multiple layers of security including network isolation using Amazon VPC, encryption at rest using keys that you create and control through AWS Key Management Service (KMS), and encryption of data in transit using SSL.
  • Fully Managed
    Aurora is fully managed by AWS, which automates time-consuming administrative tasks such as hardware provisioning, database setup, patching, and backups.
  • Compatibility
    Aurora is compatible with MySQL and PostgreSQL, making it easier to migrate existing applications to Aurora with minimal changes.

Possible disadvantages of Amazon Aurora

  • Cost
    Aurora can be more expensive than traditional RDS instances, particularly for workloads that do not fully utilize its high performance and scalability features.
  • Complexity
    The numerous features and configurations can make Aurora complex to manage and tune, especially for those who are not familiar with AWS services.
  • Vendor Lock-in
    Adopting Aurora ties you into the AWS ecosystem, which can make it difficult to migrate to other cloud providers or on-premises systems.
  • Cold Start Latency
    Aurora Serverless can experience latency during cold starts, which can be problematic for applications requiring instant scalability.
  • Limited to AWS Environment
    Aurora is only available within the AWS environment, which can be limiting if your infrastructure spans multiple cloud providers.

Analysis of Amazon Athena

Overall verdict

  • Amazon Athena is a powerful and flexible tool for users who need a cost-effective, straightforward solution for querying and analyzing data stored in S3 without the overhead of managing servers. Its serverless architecture, scalability, and wide integration with other AWS services make it a reliable choice for quick data analytics tasks.

Why this product is good

  • Amazon Athena is a serverless query service that makes it easy to analyze large-scale datasets directly in Amazon S3 using standard SQL. It is especially advantageous because it is fully managed, meaning there is no need to set up or manage infrastructure. It automatically scales, so users only pay for the queries they run, making it cost-effective for intermittent data analysis tasks. Visualizing data becomes straightforward with its integration with AWS QuickSight or other BI tools. Additionally, its support for a wide range of data formats and ease of use through the AWS Management Console further enhance its appeal for data analysts and developers.

Recommended for

  • Data analysts and data scientists needing fast, ad-hoc querying capabilities.
  • Organizations looking to reduce costs associated with traditional data warehousing.
  • Developers and teams who want to integrate SQL-based data querying into their applications without backend infrastructure management.
  • Businesses using or planning to use AWS S3 for data storage and requiring analysis tools that seamlessly integrate within the AWS ecosystem.

Analysis of Amazon Aurora

Overall verdict

  • Amazon Aurora is generally regarded as an excellent database service for businesses that require robust performance and high availability. It strikes a balance between cost-effectiveness and advanced database features, making it suitable for a wide range of applications.

Why this product is good

  • Amazon Aurora is considered a good choice for many applications due to its high performance, scalability, and compatibility with popular database systems like MySQL and PostgreSQL. It offers features like automated backups, quick failover, and replication capabilities. Aurora is designed to be fault-tolerant and highly available, providing a fully managed solution that relieves users from the operational burden associated with on-premise database management.

Recommended for

    Amazon Aurora is recommended for organizations that need reliable, scalable, and high-performance databases. It is well-suited for web and mobile applications, e-commerce platforms, real-time analytics, and other use cases requiring high availability and fault tolerance. It's ideal for businesses looking to modernize their database infrastructure and take advantage of cloud-native capabilities.

Amazon Athena videos

AWS Big Data: What is Amazon Athena?

More videos:

  • Review - Deep Dive on Amazon Athena - AWS Online Tech Talks
  • Review - Deep Dive on Amazon Athena - AWS Online Tech Talks

Amazon Aurora videos

Introduction to Amazon Aurora - Relational Database Built for the Cloud - AWS

More videos:

  • Review - Amazon Aurora Global Database Deep Dive
  • Review - What's New in Amazon Aurora - AWS Online Tech Talks

Category Popularity

0-100% (relative to Amazon Athena and Amazon Aurora)
Databases
39 39%
61% 61
Database Management
100 100%
0% 0
Relational Databases
0 0%
100% 100
Data Analysis
100 100%
0% 0

User comments

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Social recommendations and mentions

Amazon Aurora might be a bit more popular than Amazon Athena. We know about 23 links to it since March 2021 and only 23 links to Amazon Athena. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Amazon Athena mentions (23)

  • Vector: A lightweight tool for collecting EKS application logs with long-term storage capabilities
    In this article, we present an architecture that demonstrates how to collect application logs from Amazon Elastic Kubernetes Service (Amazon EKS) via Vector, store them in Amazon Simple Storage Service (Amazon S3) for long-term retention, and finally query these logs using AWS Glue and Amazon Athena. - Source: dev.to / about 1 month ago
  • Introducing Iceberg Table Engine in RisingWave: Manage Streaming Data in Iceberg with SQL
    However, Iceberg defines the storage format, leaving the complexities of data ingestion and processing, especially for real-time streams, to separate systems. While query engines like Trino or Athena excel with static datasets, they aren't designed for continuous, low-latency ingestion and transformation of streaming data into Iceberg. This often forces engineers to integrate multiple complex tools, increasing... - Source: dev.to / about 2 months ago
  • Deploying a Complete Machine Learning Fraud Detection Solution Using Amazon SageMaker : AWS Project
    SageMaker Feature Store keeps track of the metadata of stored features (e.g. Feature name or version number) so that you can query the features for the right attributes in batches or in real time using Amazon Athena , an interactive query service. - Source: dev.to / 7 months ago
  • Spatial Search of Amazon S3 Express One Zone Data with Amazon Athena and Visualized It in QGIS
    Prepare GIS data for use with Amazon Athena. This time, we created four types of sample data in QGIS in advance. - Source: dev.to / over 1 year ago
  • Enhancing AWS Athena Efficiency - Building a Python Athena Client
    If you have not heard about AWS Athena, I encourage you to take a look at this service. You can read more about it here. - Source: dev.to / over 1 year ago
View more

Amazon Aurora mentions (23)

  • Building a RAG System for Video Content Search and Analysis
    Using Amazon Bedrock to invoke Amazon Titan Foundation Models for generating multimodal embeddings, Amazon Transcribe for converting speech to text, and Amazon Aurora postgreSQL for vector storage and similarity search, you can build an application that understands both visual and audio content, enabling natural language queries to find specific moments in videos. - Source: dev.to / about 2 months ago
  • Everyone Uses Postgres… But Why?
    Cloud deployment: PostgreSQL can be deployed in the cloud with AWS RDS, Amazon Aurora, Azure Database for PostgreSQL, or Cloud SQL for PostgreSQL. - Source: dev.to / 7 months ago
  • Announcing the public beta for dedicated clusters
    Today, our Postgres databases are Amazon Aurora instances. You can trust that your database will have the scalability, reliability and security that AWS is known for. With dedicated clusters you can configure both the Postgres engine version, cluster class and number of replicas for failover and query distribution. - Source: dev.to / 10 months ago
  • Vector database is not a separate database category
    As far as the big players are concerned, Google offers AlloyDB (https://cloud.google.com/alloydb) while Amazon offers Aurora (https://aws.amazon.com/rds/aurora/). - Source: Hacker News / over 1 year ago
  • Building realtime experiences with Amazon Aurora
    Aurora is a managed database service from Amazon compatible with MySQL and PostgreSQL. It allows for the use of existing MySQL code, tools, and applications and can offer increased performance for certain workloads compared to MySQL and PostgreSQL. - Source: dev.to / almost 2 years ago
View more

What are some alternatives?

When comparing Amazon Athena and Amazon Aurora, you can also consider the following products

phpMyAdmin - phpMyAdmin is a tool written in PHP intended to handle the administration of MySQL over the Web.

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

SQLyog - Webyog develops MySQL database client tools. Monyog MySQL monitor and SQLyog MySQL GUI & admin are trusted by 2.5 million users across the globe.

MySQL - The world's most popular open source database

Sequel Pro - MySQL database management for Mac OS X

Oracle DBaaS - See how Oracle Database 12c enables businesses to plug into the cloud and power the real-time enterprise.