Amazon RDS vs Heron

Overview

Amazon RDS

Stacks16.2K

Followers10.8K

Votes761

Heron

Stacks22

Followers63

Votes4

Amazon RDS vs Heron: What are the differences?

Amazon RDS: Set up, operate, and scale a relational database in the cloud. 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; Heron: Realtime, distributed, fault-tolerant stream processing engine from Twitter. Heron is realtime analytics platform developed by Twitter. It is the direct successor of Apache Storm, built to be backwards compatible with Storm's topology API but with a wide array of architectural improvements.

Amazon RDS can be classified as a tool in the "SQL Database as a Service" category, while Heron is grouped under "Stream Processing".

Heron is an open source tool with 3.38K GitHub stars and 600 GitHub forks. Here's a link to Heron's open source repository on GitHub.

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Detailed Comparison

Amazon RDS	Heron
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.	Heron is realtime analytics platform developed by Twitter. It is the direct successor of Apache Storm, built to be backwards compatible with Storm's topology API but with a wide array of architectural improvements.
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	-
Statistics
Stacks 16.2K	Stacks 22
Followers 10.8K	Followers 63
Votes 761	Votes 4
Pros & Cons
Pros 165 Reliable failovers 156 Automated backups 130 Backed by amazon 92 Db snapshots 87 Multi-availability	Pros 1 Support most popular container environment 1 Operation friendly 1 Realtime Stream Processing 1 Highly Customizable

What are some alternatives to Amazon RDS, Heron?

Apache NiFi

An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.

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

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 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.

Apache Storm

Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.

Confluent

It is a data streaming platform based on Apache Kafka: a full-scale streaming platform, capable of not only publish-and-subscribe, but also the storage and processing of data within the stream

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.

KSQL

KSQL is an open source streaming SQL engine for Apache Kafka. It provides a simple and completely interactive SQL interface for stream processing on Kafka; no need to write code in a programming language such as Java or Python. KSQL is open-source (Apache 2.0 licensed), distributed, scalable, reliable, and real-time.

Cloud DB for Mysql

It is a fully managed cloud cache service that enables you to easily configure a MySQL database with a few settings and clicks and operate it reliably with NAVER's optimization settings, and that automatically recovers from failures.

Kafka Streams

It is a client library for building applications and microservices, where the input and output data are stored in Kafka clusters. It combines the simplicity of writing and deploying standard Java and Scala applications on the client side with the benefits of Kafka's server-side cluster technology.