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Overcoming the Storage Challenges Cassandra and Couchbase Create
A live panelist discussion on solving Cassandra and Couchbase storage challenges● Learn the Cassandra/Couchbase storage challenges● Learn the problems with typical workarounds● Design a cost effective, high performance solution
On Demand Webinar
For audio playback and Q&A go to:http://bit.ly/OvercomeCass
Our SpeakersGeorge Crump is the founder of Storage Switzerland, the leading storage analyst focused on the subjects of big data, solid state storage, virtualization, cloud computing and data protection.
He is widely recognized for his articles, white papers, and videos on such current approaches as all-flash arrays, deduplication, SSDs, software-defined storage, backup appliances, and storage networking. He has 25 years of experience designing storage solutions for data centers across the US.
● Analyst firm focused on storage, cloud and virtualization
● Knowledge of these markets is gained through product testing and interaction with end users and suppliers
● The results of this research can be found in the articles, videos, webinars, product analysis and case studies on our web site:http://storageswiss.com
Who Is Storage Switzerland?
Our SpeakersSharon Azulai – CEO
Sharon is an experienced entrepreneur with a proven track record in leading strategy, market positioning and go-to-market for startup companies.
Dr. Amit Golander – CTO
Amit leads IT infrastructure innovations for the past decade and a half. This includes research and development, across storage, servers and networks.
Plexistor brings enterprise grade storage features such as high availability and snapshots to big data applications like Cassandra, Couchbase, and Spark enabling massive server consolidation and fast recovery time.
What Is Cassandra And Couchbase?● Cassandra is essentially a wide-row/column store NoSQL
database management system
● Couchbase is essentially a document NoSQL database management system
Distributed Databases
Highly Scalable
High Performance
Why Are Organizations Adopting Them?
• Changing needs - The era of now
• Traditional databases cannot deliver the required performance
• Support NoSQL as well as SQL and are expanding to built in support for indexing, graphs, streams and the like
• Horizontal scale on commodity hardware
• Execute code next to the data
How Is Their Internal Storage Architecture Different From Traditional Databases?
Distributed Architecture
Node Failure
Take over by other machines in the cluster
Cluster In Rebuild State
• Assumes that the active data set fits into the aggregated memory
• Expensive
• Finite resource per machine
• Memory is volatile
• Data at temporal risk
• Long warm-up time on failure
What Are The Storage Challenges That Cassandra And Couchbase Create?
What Happens When It Runs Out Of Memory
• Spill to storage via Linux POSIX
• Storage is the bottleneck
• SSD is faster than HDD, but still x1000 times slower than memory
• Over-provision servers• High aggregated Memory budget
• Cover the peak working set size
• Use Flash storage• At least for the CommitLog
• Data must still go through Linux I/O Stack
• Poor latency under heavy IOPS load
• Expensive
How Organization Attempt To Workaround These Challenges
• Replace I/O Stack with one that can perform at near-memory speed
• Low-latency storage can reduce server count
• Persistent storage can reduce recovery time in case of a node failure
• In Couchbase we can eliminate the local persistency and the transaction log to further improve performance
How To Design A Solution To These Challenges Instead Of A Workaround
Plexistor Solution
Product Overview
Memory & Storage Convergence
Product Architecture
Performance is highly sensitive to persistency/durability requirementsReplication between nodes without persistency is vulnerable to Power Failures
Data loss risk is often not well explained. Confusion leads to wasteful behavior (#copies, Network)
Zero Cost Persistency
How Fast is Fast Storage?
Measured on the same SCM Hardware & Kernel
Software is the differentiator!
How Fast is Fast Storage?
Note that each Database use case is unique, so table rows are incomparable
QoS and Efficiency Comparison
Visit for the latest downloads, white papers, SDM blogs and
Tech Field Day videos
Additional Resources
Thank you!Storage Switzerlandhttp://[email protected]
StorageSwiss on Twitter:http://twitter.com/storageswiss
StorageSwiss on YouTube:http://www.youtube.com/user/storageswiss
Plexistorhttp://www.plexistor.com
Plexistor on Twitter:http://twitter.com/plexistor
Plexistor on LinkedIN:http://www.linkedin/company/plexistor
Overcoming the Storage Challenges Cassandra and Couchbase Create
For Complete Audio and Q&A please registerfor the On-Demand Version at
http://bit.ly/OvercomeCass
