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Cassandra

A partitioned row store. Rows are organized into tables with a required primary key.
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What is Cassandra?

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
Cassandra is a tool in the Databases category of a tech stack.
Cassandra is an open source tool with 5.6K GitHub stars and 2.5K GitHub forks. Here鈥檚 a link to Cassandra's open source repository on GitHub

Who uses Cassandra?

Companies
447 companies reportedly use Cassandra in their tech stacks, including Uber, Facebook, and Netflix.

Developers
1607 developers on StackShare have stated that they use Cassandra.

Cassandra Integrations

Datadog, Server Density, Boundary, Presto, and SignalFx are some of the popular tools that integrate with Cassandra. Here's a list of all 34 tools that integrate with Cassandra.

Why developers like Cassandra?

Here鈥檚 a list of reasons why companies and developers use Cassandra
Cassandra Reviews

Here are some stack decisions, common use cases and reviews by companies and developers who chose Cassandra in their tech stack.

Jean Francois Rebaud
Jean Francois Rebaud
Kubernetes
Kubernetes
GitLab CI
GitLab CI
Cassandra
Cassandra
ExpressJS
ExpressJS
Angular 2
Angular 2

Kubernetes GitLab CI Cassandra ExpressJS Angular 2

I start a new project of a plateform to make an iventory of bands in my musical style preference I choose

  1. for the BackEnd: Express, Casssandra Express because I want to use API and compatibilitie with others front plateform and Cassandra about is performance of scalability

  2. for the Frontend: Angular because it's a real framework and this structure is perfect to add and update new features to make easily evolution

It's the begening of the project and I'll come back for future informations and discussion about problems that must resolved

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Chris McFadden
Chris McFadden
VP, Engineering at SparkPost | 5 upvotes 22.4K views
atSparkPostSparkPost
Cassandra
Cassandra
Amazon DynamoDB
Amazon DynamoDB
Amazon RDS for Aurora
Amazon RDS for Aurora

We migrated most of our APIs last year from using our self managed Cassandra cluster to a mix of Amazon DynamoDB and Amazon RDS for Aurora. This has reduced the operational overhead for our team and greatly improved the overall reliability of our service. The new dynamic capacity in DynamoDB has been super helpful for handling bursty traffic.

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StackShare Editors
StackShare Editors
| 4 upvotes 64.4K views
atUber TechnologiesUber Technologies
Cassandra
Cassandra
Apache Spark
Apache Spark
TensorFlow
TensorFlow

In mid-2015, Uber began exploring ways to scale ML across the organization, avoiding ML anti-patterns while standardizing workflows and tools. This effort led to Michelangelo.

Michelangelo consists of a mix of open source systems and components built in-house. The primary open sourced components used are HDFS, Spark, Samza, Cassandra, MLLib, XGBoost, and TensorFlow.

!

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Tobias Widmer
Tobias Widmer
CTO at Onedot | 4 upvotes 44.1K views
atOnedotOnedot
React
React
Redux
Redux
Scala
Scala
TypeScript
TypeScript
Cassandra
Cassandra
Apache Spark
Apache Spark
Amazon S3
Amazon S3
Blueprint
Blueprint
npm
npm

Onedot is building an automated data preparation service using probabilistic and statistical methods including artificial intelligence (AI). From the beginning, having a stable foundation while at the same time being able to iterate quickly was very important to us. Due to the nature of compute workloads we face, the decision for a functional programming paradigm and a scalable cluster model was a no-brainer. We started playing with Apache Spark very early on, when the platform was still in its infancy. As a storage backend, we first used Cassandra, but found out that it was not the optimal choice for our workloads (lots of rather smallish datasets, data pipelines with considerable complexity, etc.). In the end, we migrated dataset storage to Amazon S3 which proved to be much more adequate to our case. In the frontend, we bet on more traditional frameworks like React/Redux.js, Blueprint and a number of common npm packages of our universe. Because of the very positive experience with Scala (in particular the ability to write things very expressively, use immutability across the board, etc.) we settled with TypeScript in the frontend. In our opinion, a very good decision. Nowadays, transpiling is a common thing, so we thought why not introduce the same type-safety and mathematical rigour to the user interface?

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Naresh Kancharla
Naresh Kancharla
Staff Engineer at Nutanix | 2 upvotes 14.8K views
atCyanogenCyanogen
Cassandra
Cassandra

I use Cassandra because scales horizontally at ease. Provides availability and partition tolerance. Cassandra can be used only if we know upfront all the read patterns on the data.

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StackShare Editors
StackShare Editors
Cassandra
Cassandra
AWS EC2
AWS EC2

On June 3, 2014 PagerDuty experienced a major issue: their Cassandra pipeline had stopped processing events and refused new ones. All in all, an outage was created that lasted 3 hours, along with additional degraded performance.

"Cassandra seems to have two modes: fine and catastrophe" said one of the PagerDuty engineers, as a seemingly routine repair had cascaded into a very bad situation. Constant memory pressure and underprovisioned amounts of RAM were isolated as a few of the factors that pointed to weaknesses in the way the cluster was set up.

After the outage, each node in the Cassandra cluster was replaced with m2.2xlarge EC2 nodes with 4 cores and 32GB of RAM. PagerDuty also moved away from using a multi-tenant Cassandra setup at that point, to help isolate failures in the future.

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Cassandra Alternatives & Comparisons

What are some alternatives to Cassandra?
HBase
Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop.
Hadoop
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
Redis
Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.
Couchbase
Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
See all alternatives

Cassandra's Followers
1622 developers follow Cassandra to keep up with related blogs and decisions.
Niral Koradia
Parviz Rozikov
nadav00124833
Alex Gauthier
呕aneta Ja偶d偶yk
ayonsaha2011
Garey Hoffman
Marvin Collins
Lalit Nayyar
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