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Amazon Kinesis vs Firehose.io: What are the differences?
What is Amazon Kinesis? Store and process terabytes of data each hour from hundreds of thousands of sources. Amazon Kinesis can collect and process hundreds of gigabytes of data per second from hundreds of thousands of sources, allowing you to easily write applications that process information in real-time, from sources such as web site click-streams, marketing and financial information, manufacturing instrumentation and social media, and operational logs and metering data.
What is Firehose.io? Build realtime Ruby web applications. Firehose is both a Rack application and JavaScript library that makes building real-time web applications possible.
Amazon Kinesis can be classified as a tool in the "Real-time Data Processing" category, while Firehose.io is grouped under "Realtime Backend / API".
Some of the features offered by Amazon Kinesis are:
- Real-time Processing- Amazon Kinesis enables you to collect and analyze information in real-time, allowing you to answer questions about the current state of your data, from inventory levels to stock trade frequencies, rather than having to wait for an out-of-date report.
- Easy to use- You can create a new stream, set the throughput requirements, and start streaming data quickly and easily. Amazon Kinesis automatically provisions and manages the storage required to reliably and durably collect your data stream.
- High throughput. Elastic.- Amazon Kinesis seamlessly scales to match the data throughput rate and volume of your data, from megabytes to terabytes per hour. Amazon Kinesis will scale up or down based on your needs.
On the other hand, Firehose.io provides the following key features:
- Firehose embraces RESTful design prinicpals and consequently works great with any library that speaks HTTP
- Integrates with Backbone.js and Ember.js
- Hook it into an ORM, like ActiveRecord
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Learn MorePros of Amazon Kinesis
Pros of Firehose.io
Pros of Amazon Kinesis
- Scalable9
Pros of Firehose.io
- RESTful2
- Rails gem2
- Works with ActiveRecord2
- Clean way to build real-time web applications1
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Cons of Amazon Kinesis
Cons of Firehose.io
Cons of Amazon Kinesis
- Cost3
Cons of Firehose.io
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What is Amazon Kinesis?
Amazon Kinesis can collect and process hundreds of gigabytes of data per second from hundreds of thousands of sources, allowing you to easily write applications that process information in real-time, from sources such as web site click-streams, marketing and financial information, manufacturing instrumentation and social media, and operational logs and metering data.
What is Firehose.io?
Firehose is both a Rack application and JavaScript library that makes building real-time web applications possible.
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What companies use Amazon Kinesis?
What companies use Firehose.io?
What companies use Firehose.io?
See which teams inside your own company are using Amazon Kinesis or Firehose.io.
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What tools integrate with Amazon Kinesis?
What tools integrate with Firehose.io?
What tools integrate with Amazon Kinesis?
What tools integrate with Firehose.io?
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What are some alternatives to Amazon Kinesis and Firehose.io?
Kafka
Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
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.
Amazon SQS
Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.
Amazon Kinesis Firehose
Amazon Kinesis Firehose is the easiest way to load streaming data into AWS. It can capture and automatically load streaming data into Amazon S3 and Amazon Redshift, enabling near real-time analytics with existing business intelligence tools and dashboards you’re already using today.
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.