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  1. Stackups
  2. Application & Data
  3. Relational Databases
  4. SQL Database As A Service
  5. Amazon EMR vs Amazon RDS

Amazon EMR vs Amazon RDS

OverviewComparisonAlternatives

Overview

Amazon RDS
Amazon RDS
Stacks16.2K
Followers10.8K
Votes761
Amazon EMR
Amazon EMR
Stacks543
Followers682
Votes54

Amazon EMR vs Amazon RDS: What are the differences?

Introduction

In this markdown, I will provide the key differences between Amazon EMR and Amazon RDS, two popular services offered by Amazon Web Services (AWS) for data processing and database management, respectively.

  1. Scalability and Data Processing: Amazon EMR (Elastic MapReduce) is designed for big data processing and analytics. It allows users to easily process and analyze large amounts of structured and unstructured data using popular frameworks like Apache Spark and Hadoop. On the other hand, Amazon RDS (Relational Database Service) is a managed database service that offers scalable and reliable relational database management systems (RDBMS) like MySQL, PostgreSQL, and Oracle. It is optimized for online transaction processing (OLTP) workloads where data consistency and transactional capabilities are crucial.

  2. Data Storage: In Amazon EMR, data is usually stored in Amazon S3 (Simple Storage Service), an object storage service offered by AWS. This allows users to separate compute and storage, making it easier to handle large volumes of data. On the other hand, Amazon RDS provides a managed storage solution where data is stored within the RDS service itself. The storage capacity of Amazon RDS is determined by the instance class chosen.

  3. Data Processing Frameworks: Amazon EMR supports popular big data processing frameworks such as Apache Hadoop, Apache Spark, and Apache Hive. These frameworks enable distributed processing of data and provide a wide range of tools for data transformation, analysis, and visualization. In contrast, Amazon RDS primarily focuses on providing managed relational database services and does not support big data processing frameworks out of the box.

  4. Managed vs Self-Managed: Amazon EMR is a fully managed service that takes care of infrastructure provisioning, software installations, and cluster management. Users can easily launch EMR clusters and start processing data without worrying about the underlying infrastructure. On the other hand, Amazon RDS also offers a managed service, but it requires users to manage their own database instances. While Amazon RDS handles tasks like backups, failover, and software patching, users are responsible for configuring and managing their database instances.

  5. Pricing Model: The pricing model for Amazon EMR is based on the size and number of EC2 instances in the cluster, along with additional charges for storage and data transfer. The cost is calculated based on the usage duration. On the other hand, Amazon RDS pricing is based on the type and size of the database instance, along with additional charges for storage and data transfer. The cost is calculated on an hourly basis.

  6. Use Cases: Amazon EMR is well-suited for big data processing and analytics use cases such as log analysis, data warehousing, machine learning, and large-scale data transformations. It provides the flexibility to process large datasets using distributed computing frameworks. On the other hand, Amazon RDS is ideal for applications that require a traditional relational database management system, such as e-commerce platforms, content management systems, and business applications that rely on structured data and transactions.

In summary, Amazon EMR is designed for big data processing and analytics, offering scalability, data processing frameworks, and the ability to separate compute and storage. Amazon RDS, on the other hand, focuses on managed relational database services with scalability, data consistency, and transactional capabilities for traditional database applications.

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Detailed Comparison

Amazon RDS
Amazon RDS
Amazon EMR
Amazon EMR

Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.

It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.

Pre-configured Parameters;Monitoring and Metrics;Automatic Software Patching;Automated Backups;DB Snapshots;DB Event Notifications;Multi-Availability Zone (Multi-AZ) Deployments;Provisioned IOPS;Push-Button Scaling;Automatic Host Replacement;Replication;Isolation and Security
Elastic- Amazon EMR enables you to quickly and easily provision as much capacity as you need and add or remove capacity at any time. Deploy multiple clusters or resize a running cluster;Low Cost- Amazon EMR is designed to reduce the cost of processing large amounts of data. Some of the features that make it low cost include low hourly pricing, Amazon EC2 Spot integration, Amazon EC2 Reserved Instance integration, elasticity, and Amazon S3 integration.;Flexible Data Stores- With Amazon EMR, you can leverage multiple data stores, including Amazon S3, the Hadoop Distributed File System (HDFS), and Amazon DynamoDB.;Hadoop Tools- EMR supports powerful and proven Hadoop tools such as Hive, Pig, and HBase.
Statistics
Stacks
16.2K
Stacks
543
Followers
10.8K
Followers
682
Votes
761
Votes
54
Pros & Cons
Pros
  • 165
    Reliable failovers
  • 156
    Automated backups
  • 130
    Backed by amazon
  • 92
    Db snapshots
  • 87
    Multi-availability
Pros
  • 15
    On demand processing power
  • 12
    Don't need to maintain Hadoop Cluster yourself
  • 7
    Hadoop Tools
  • 6
    Elastic
  • 4
    Backed by Amazon

What are some alternatives to Amazon RDS, Amazon EMR?

Google BigQuery

Google BigQuery

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

Amazon Redshift

Amazon Redshift

It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.

Qubole

Qubole

Qubole is a cloud based service that makes big data easy for analysts and data engineers.

Amazon Aurora

Amazon Aurora

Amazon Aurora is a MySQL-compatible, relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora provides up to five times better performance than MySQL at a price point one tenth that of a commercial database while delivering similar performance and availability.

Google Cloud SQL

Google Cloud SQL

Run the same relational databases you know with their rich extension collections, configuration flags and developer ecosystem, but without the hassle of self management.

ClearDB

ClearDB

ClearDB uses a combination of advanced replication techniques, advanced cluster technology, and layered web services to provide you with a MySQL database that is "smarter" than usual.

Altiscale

Altiscale

we run Apache Hadoop for you. We not only deploy Hadoop, we monitor, manage, fix, and update it for you. Then we take it a step further: We monitor your jobs, notify you when something’s wrong with them, and can help with tuning.

Snowflake

Snowflake

Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.

Azure SQL Database

Azure SQL Database

It is the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software.

Stitch

Stitch

Stitch is a simple, powerful ETL service built for software developers. Stitch evolved out of RJMetrics, a widely used business intelligence platform. When RJMetrics was acquired by Magento in 2016, Stitch was launched as its own company.

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