Amazon Athena vs Redis

Overview

Redis

Stacks61.9K

Followers46.5K

Votes3.9K

GitHub Stars42

Forks6

Amazon Athena

Stacks521

Followers840

Votes49

Amazon Athena vs Redis: What are the differences?

Introduction

Amazon Athena and Redis are both popular technologies used in building and managing various applications. Each of them has distinct features and use cases that differentiate them from each other. In this article, we will explore the key differences between Amazon Athena and Redis.

1. Data Storage Model: Amazon Athena is a serverless interactive query service that enables analyzing data directly from Amazon S3 using SQL. It is primarily designed for querying structured and semi-structured data. On the other hand, Redis is an in-memory data structure store that can be used as a database, cache, or message broker. It stores data in key-value pairs, allowing for quick access and manipulation of data.
2. Data Processing: Amazon Athena is focused on ad-hoc query processing and analysis. It excels in running complex SQL queries and leveraging the power of SQL-based analytics tools. Redis, on the other hand, is primarily used for real-time data processing and caching. It provides high-performance data manipulation capabilities and can execute operations such as reads, writes, and computations on the data stored in memory.
3. Scalability and Elasticity: Amazon Athena is a fully managed service that automatically scales resources based on the query load. It can handle large volumes of data and concurrent user queries efficiently. Redis, on the other hand, can be deployed in a cluster configuration, allowing for horizontal scalability to handle high workloads. It provides data partitioning and replication options for increased performance and fault tolerance.
4. Durability and Persistence: Amazon Athena does not provide persistent storage. It directly queries data stored in Amazon S3 without the need for data duplication. On the other hand, Redis provides various persistence options, including snapshots and append-only files. This allows Redis to persist data on disk and recover it in case of system failures or restarts.
5. Data Types and Functionality: Amazon Athena supports a wide range of SQL data types and functions for querying and analyzing data. It also integrates with various other AWS services for data ingestion and transformation. Redis, on the other hand, provides a rich set of in-memory data types such as strings, lists, sets, hashes, and sorted sets. It also supports advanced data manipulation operations like pub/sub messaging and geospatial queries.
6. Cost and Pricing Model: Amazon Athena follows a pay-per-query pricing model, where you only pay for the amount of data scanned by your queries. The pricing can vary based on the amount and complexity of your queries. Redis can be deployed on various cloud providers or on-premises, and its pricing depends on factors such as the instance size, storage capacity, and network usage.

In summary, Amazon Athena is a serverless query service designed for structured and semi-structured data analysis, while Redis is an in-memory data structure store used for real-time data processing and caching. Athena excels in complex SQL queries and integrates with AWS services, while Redis provides high-performance data manipulation and offers various persistence options. The choice between the two depends on your specific use case and requirements.

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Advice on Redis, Amazon Athena

Pavithra

Mar 12, 2020

Needs adviceon

Amazon S3

Amazon Athena

Amazon Redshift

Hi all,

Currently, we need to ingest the data from Amazon S3 to DB either Amazon Athena or Amazon Redshift. But the problem with the data is, it is in .PSV (pipe separated values) format and the size is also above 200 GB. The query performance of the timeout in Athena/Redshift is not up to the mark, too slow while compared to Google BigQuery. How would I optimize the performance and query result time? Can anyone please help me out?

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Detailed Comparison

Redis	Amazon Athena
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.	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.
Statistics
GitHub Stars 42	GitHub Stars -
GitHub Forks 6	GitHub Forks -
Stacks 61.9K	Stacks 521
Followers 46.5K	Followers 840
Votes 3.9K	Votes 49
Pros & Cons
Pros 888 Performance 542 Super fast 514 Ease of use 444 In-memory cache 324 Advanced key-value cache Cons 15 Cannot query objects directly 3 No secondary indexes for non-numeric data types 1 No WAL	Pros 16 Use SQL to analyze CSV files 8 Glue crawlers gives easy Data catalogue 7 Cheap 6 Query all my data without running servers 24x7 4 No data base servers yay
Integrations
No integrations available	Amazon S3 Presto

What are some alternatives to Redis, Amazon Athena?

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Presto

Distributed SQL Query Engine for Big Data

Hazelcast

With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.

Aerospike

Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees.

MemSQL

MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines.

Apache Ignite

It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale

Apache Flink

Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.

lakeFS

It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.

Druid

Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

SAP HANA

It is an application that uses in-memory database technology that allows the processing of massive amounts of real-time data in a short time. The in-memory computing engine allows it to process data stored in RAM as opposed to reading it from a disk.

Related Comparisons

Amazon Athena vs Redis: What are the differences?

Introduction

1. Data Storage Model: Amazon Athena is a serverless interactive query service that enables analyzing data directly from Amazon S3 using SQL. It is primarily designed for querying structured and semi-structured data. On the other hand, Redis is an in-memory data structure store that can be used as a database, cache, or message broker. It stores data in key-value pairs, allowing for quick access and manipulation of data.
2. Data Processing: Amazon Athena is focused on ad-hoc query processing and analysis. It excels in running complex SQL queries and leveraging the power of SQL-based analytics tools. Redis, on the other hand, is primarily used for real-time data processing and caching. It provides high-performance data manipulation capabilities and can execute operations such as reads, writes, and computations on the data stored in memory.
3. Scalability and Elasticity: Amazon Athena is a fully managed service that automatically scales resources based on the query load. It can handle large volumes of data and concurrent user queries efficiently. Redis, on the other hand, can be deployed in a cluster configuration, allowing for horizontal scalability to handle high workloads. It provides data partitioning and replication options for increased performance and fault tolerance.
4. Durability and Persistence: Amazon Athena does not provide persistent storage. It directly queries data stored in Amazon S3 without the need for data duplication. On the other hand, Redis provides various persistence options, including snapshots and append-only files. This allows Redis to persist data on disk and recover it in case of system failures or restarts.
5. Data Types and Functionality: Amazon Athena supports a wide range of SQL data types and functions for querying and analyzing data. It also integrates with various other AWS services for data ingestion and transformation. Redis, on the other hand, provides a rich set of in-memory data types such as strings, lists, sets, hashes, and sorted sets. It also supports advanced data manipulation operations like pub/sub messaging and geospatial queries.
6. Cost and Pricing Model: Amazon Athena follows a pay-per-query pricing model, where you only pay for the amount of data scanned by your queries. The pricing can vary based on the amount and complexity of your queries. Redis can be deployed on various cloud providers or on-premises, and its pricing depends on factors such as the instance size, storage capacity, and network usage.

Amazon Athena vs Redis

Overview

Amazon Athena vs Redis: What are the differences?