Apache Flink vs Azure Storage

Overview

Azure Storage

Stacks1.3K

Followers787

Votes52

Apache Flink

Stacks534

Followers879

Votes38

GitHub Stars25.4K

Forks13.7K

Azure Storage vs Apache Flink: What are the differences?

What is Azure Storage? Reliable, economical cloud storage for data big and small. Azure Storage provides the flexibility to store and retrieve large amounts of unstructured data, such as documents and media files with Azure Blobs; structured nosql based data with Azure Tables; reliable messages with Azure Queues, and use SMB based Azure Files for migrating on-premises applications to the cloud.

What is Apache Flink? Fast and reliable large-scale data processing engine. 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.

Azure Storage and Apache Flink are primarily classified as "Cloud Storage" and "Big Data" tools respectively.

Some of the features offered by Azure Storage are:

Blobs, Tables, Queues, and Files
Highly scalable
Durable & highly available

On the other hand, Apache Flink provides the following key features:

Hybrid batch/streaming runtime that supports batch processing and data streaming programs.
Custom memory management to guarantee efficient, adaptive, and highly robust switching between in-memory and data processing out-of-core algorithms.
Flexible and expressive windowing semantics for data stream programs

"All-in-one storage solution" is the top reason why over 18 developers like Azure Storage, while over 6 developers mention "Unified batch and stream processing" as the leading cause for choosing Apache Flink.

Apache Flink is an open source tool with 9.35K GitHub stars and 5K GitHub forks. Here's a link to Apache Flink's open source repository on GitHub.

According to the StackShare community, Azure Storage has a broader approval, being mentioned in 84 company stacks & 44 developers stacks; compared to Apache Flink, which is listed in 20 company stacks and 22 developer stacks.

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Advice on Azure Storage, Apache Flink

Nilesh

Technical Architect at Self Employed

Jul 8, 2020

Needs adviceon

Elasticsearch

Kafka

We have a Kafka topic having events of type A and type B. We need to perform an inner join on both type of events using some common field (primary-key). The joined events to be inserted in Elasticsearch.

In usual cases, type A and type B events (with same key) observed to be close upto 15 minutes. But in some cases they may be far from each other, lets say 6 hours. Sometimes event of either of the types never come.

In all cases, we should be able to find joined events instantly after they are joined and not-joined events within 15 minutes.

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Comments

Detailed Comparison

Azure Storage	Apache Flink
Azure Storage provides the flexibility to store and retrieve large amounts of unstructured data, such as documents and media files with Azure Blobs; structured nosql based data with Azure Tables; reliable messages with Azure Queues, and use SMB based Azure Files for migrating on-premises applications to the cloud.	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.
Blobs, Tables, Queues, and Files;Highly scalable;Durable & highly available;Premium Storage;Designed for developers	Hybrid batch/streaming runtime that supports batch processing and data streaming programs.;Custom memory management to guarantee efficient, adaptive, and highly robust switching between in-memory and data processing out-of-core algorithms.;Flexible and expressive windowing semantics for data stream programs;Built-in program optimizer that chooses the proper runtime operations for each program;Custom type analysis and serialization stack for high performance
Statistics
GitHub Stars -	GitHub Stars 25.4K
GitHub Forks -	GitHub Forks 13.7K
Stacks 1.3K	Stacks 534
Followers 787	Followers 879
Votes 52	Votes 38
Pros & Cons
Pros 24 All-in-one storage solution 15 Pay only for data used regardless of disk size 9 Shared drive mapping 2 Cheapest hot and cloud storage 2 Cost-effective Cons 2 Direct support is not provided by Azure storage	Pros 16 Unified batch and stream processing 8 Out-of-the box connector to kinesis,s3,hdfs 8 Easy to use streaming apis 4 Open Source 2 Low latency
Integrations
Microsoft Azure	YARN Hadoop Hadoop HBase Kafka

What are some alternatives to Azure Storage, Apache Flink?

Amazon S3

Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web

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 EBS

Amazon EBS volumes are network-attached, and persist independently from the life of an instance. Amazon EBS provides highly available, highly reliable, predictable storage volumes that can be attached to a running Amazon EC2 instance and exposed as a device within the instance. Amazon EBS is particularly suited for applications that require a database, file system, or access to raw block level storage.

Google Cloud Storage

Google Cloud Storage allows world-wide storing and retrieval of any amount of data and at any time. It provides a simple programming interface which enables developers to take advantage of Google's own reliable and fast networking infrastructure to perform data operations in a secure and cost effective manner. If expansion needs arise, developers can benefit from the scalability provided by Google's infrastructure.

Presto

Distributed SQL Query Engine for Big Data

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.

Minio

Minio is an object storage server compatible with Amazon S3 and licensed under Apache 2.0 License

OpenEBS

OpenEBS allows you to treat your persistent workload containers, such as DBs on containers, just like other containers. OpenEBS itself is deployed as just another container on your host.

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.

Related Comparisons

Some of the features offered by Azure Storage are:

Blobs, Tables, Queues, and Files
Highly scalable
Durable & highly available

On the other hand, Apache Flink provides the following key features:

Hybrid batch/streaming runtime that supports batch processing and data streaming programs.
Custom memory management to guarantee efficient, adaptive, and highly robust switching between in-memory and data processing out-of-core algorithms.
Flexible and expressive windowing semantics for data stream programs

Apache Flink is an open source tool with 9.35K GitHub stars and 5K GitHub forks. Here's a link to Apache Flink's open source repository on GitHub.

Apache Flink vs Azure Storage