Google Cloud Storage vs Kudu

Overview

Google Cloud Storage

Stacks2.0K

Followers1.2K

Votes75

Apache Kudu

Stacks71

Followers259

Votes10

GitHub Stars828

Forks282

Google Cloud Storage vs Kudu: What are the differences?

What is Google Cloud Storage? Durable and highly available object storage service. 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.

What is Kudu? Fast Analytics on Fast Data. A columnar storage manager developed for the Hadoop platform. A new addition to the open source Apache Hadoop ecosystem, Kudu completes Hadoop's storage layer to enable fast analytics on fast data.

Google Cloud Storage belongs to "Cloud Storage" category of the tech stack, while Kudu can be primarily classified under "Big Data Tools".

"Scalable" is the primary reason why developers consider Google Cloud Storage over the competitors, whereas "Realtime Analytics" was stated as the key factor in picking Kudu.

Kudu is an open source tool with 789 GitHub stars and 263 GitHub forks. Here's a link to Kudu's open source repository on GitHub.

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Advice on Google Cloud Storage, Apache Kudu

Gabriel

CEO at NaoLogic Inc

Dec 24, 2019

Decided

We offer our customer HIPAA compliant storage. After analyzing the market, we decided to go with Google Storage. The Nodejs API is ok, still not ES6 and can be very confusing to use. For each new customer, we created a different bucket so they can have individual data and not have to worry about data loss. After 1000+ customers we started seeing many problems with the creation of new buckets, with saving or retrieving a new file. Many false positive: the Promise returned ok, but in reality, it failed.

That's why we switched to S3 that just works.

330k views330k

Comments

Ben

May 18, 2020

Decided

We choose Backblaze B2 because it makes more sense for storing static assets.

We admire Backblaze's customer service & transparency, plus, we trust them to maintain fair business practices - including not raising prices in the future.

Lower storage costs means we can keep more data for longer, and lower bandwidth means cache misses don't cost a ton.

120k views120k

Comments

Detailed Comparison

Google Cloud Storage	Apache Kudu
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.	A new addition to the open source Apache Hadoop ecosystem, Kudu completes Hadoop's storage layer to enable fast analytics on fast data.
High Capacity and Scalability;Strong Data Consistency;Google Developers Console Projects;Bucket Locations;REST APIS;OAuth 2.0 Authentication;Authenticated Browser Downloads;Google Account Support for Sharing	-
Statistics
GitHub Stars -	GitHub Stars 828
GitHub Forks -	GitHub Forks 282
Stacks 2.0K	Stacks 71
Followers 1.2K	Followers 259
Votes 75	Votes 10
Pros & Cons
Pros 28 Scalable 19 Cheap 14 Reliable 9 Easy 3 Chealp	Pros 10 Realtime Analytics Cons 1 Restart time
Integrations
No integrations available	Hadoop

What are some alternatives to Google Cloud Storage, Apache Kudu?

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.

Presto

Distributed SQL Query Engine for Big Data

Azure Storage

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.

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.

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.

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Google Cloud Storage vs Kudu: What are the differences?

Google Cloud Storage belongs to "Cloud Storage" category of the tech stack, while Kudu can be primarily classified under "Big Data Tools".

"Scalable" is the primary reason why developers consider Google Cloud Storage over the competitors, whereas "Realtime Analytics" was stated as the key factor in picking Kudu.

Kudu is an open source tool with 789 GitHub stars and 263 GitHub forks. Here's a link to Kudu's open source repository on GitHub.