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<divclass="well see-also">Apache Cassandra is an implementation of the <ahref="/no-sql-datastore.html">NoSQL database</a> concept. Learn more in the <ahref="/data.html">data</a> chapter or view the <ahref="/table-of-contents.html">table of contents</a> for all topics.</div>
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the HTTP request-response cycle to prevent timeouts and blocking issues with
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[WSGI servers](/wsgi-servers.html).
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* The Stack Overflow thread asking about the
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[best Cassandra library/driver for Python?](https://stackoverflow.com/questions/10430417/best-cassandra-library-wrapper-for-python)
project due to its CQL support and active development.
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## How Companies Use Cassandra
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These resources are written by engineering teams at organizations that
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have large scale Cassandra deployments. The posts cover topics such as
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monitoring, scaling and usage with billions of records.
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*[How Discord Stores Billions of Messages](https://blog.discordapp.com/how-discord-stores-billions-of-messages-7fa6ec7ee4c7)
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talks about the evolution of Discord's very large scale message store
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system from a [MongoDB](/mongodb.html) instance to Cassandra for storing
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messages in a distributed, replicated cluster.
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*[Monitoring Cassandra at Scale](http://engineeringblog.yelp.com/2016/06/monitoring-cassandra-at-scale.html)
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explains how the Yelp engineering team uses Cassandra to complement their
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MySQL and ElasticSearch instances. The post does a nice job of enumerating
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the warning signs to monitor and provides a short example of an issue with
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replication that could be caught by their approach.
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*[How Uber Manages A Million Writes Per Second Using Mesos And Cassandra Across Multiple Datacenters ](http://highscalability.com/blog/2016/9/28/how-uber-manages-a-million-writes-per-second-using-mesos-and.html)
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shows why Uber needs accurate real-time data at large scale to make their
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driver and passenger operations run properly. The post goes into the
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overall architecture they use including cluster size, tolerable latency
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and other libraries in their stack.
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## General Cassandra resources
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Apache Cassandra can be used independently of Python applications for
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[getting started documentation for Cassandra](http://cassandra.apache.org/doc/latest/getting_started/index.html)
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provides installation, configuration, and basic querying information.
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*[Monitoring Cassandra at Scale](http://engineeringblog.yelp.com/2016/06/monitoring-cassandra-at-scale.html)
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explains how the Yelp engineering team uses Cassandra to complement their
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MySQL and ElasticSearch instances. The post does a nice job of enumerating
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the warning signs to monitor and provides a short example of an issue with
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replication that could be caught by their approach.
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*[How Not To Use Cassandra Like An RDBMS (and what will happen if you do)](https://opencredo.com/how-not-to-use-cassandra-like-an-rdbms-and-what-will-happen-if-you-do/)
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gives examples in Cassandra's query language CQL of operations that are
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typical with [relational databases](/databases.html) but go *terribly* wrong
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with Cassandra, due to its NoSQL architecture that is optimized for other
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types of operations.
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*[Backup and Recovery for Apache Cassandra and Scale-Out Databases](https://www.youtube.com/watch?v=krGmn4D2fgY)
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covers issues encountered when trying to take snapshot backups of Cassandra
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due to partitions and consistency lag time that occur with just about every
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is a video for on data modeling and application development for developers
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new to Cassandra.
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*[How Discord Stores Billions of Messages](https://blog.discordapp.com/how-discord-stores-billions-of-messages-7fa6ec7ee4c7)
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talks about the evolution of Discord's very large scale message store
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system from a [MongoDB](/mongodb.html) instance to Cassandra for storing
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messages in a distributed, replicated cluster.
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*[The Total Newbie’s Guide to Cassandra](https://blog.insightdatascience.com/the-total-newbies-guide-to-cassandra-e63bce0316a4)
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compares Cassandra to traditional [relational databases](/databases.html).
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*[On Cassandra Collections, Updates, and Tombstones](https://www.sestevez.com/on-cassandra-collections-updates-and-tombstones/)
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presents a mistake of using collections in the wrong way that developers
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often make when using Cassandra for the first time.
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*[When to use Cassandra and when to steer clear](https://towardsdatascience.com/when-to-use-cassandra-and-when-to-steer-clear-72b7f2cede76)
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explains the advantages Cassandra provides such as high throughput on
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writes (versus reads) and availability. The disadvantages are also
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given such as strong consistency, typical relational database-style
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(ACID) transactions and reads without knowing the primary key of the
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record you want to access. These are common database tradeoffs you need
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to understand based on your workload and decide upon *before* you build
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