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2 .Contents
1. Introduction to NoSQL systems, Extensible Record Stores and Amazon’s Dynamo
+ Google Bigtable
2. What Cassandra is and how it is compared with other similar systems
3. What applications are better supported - examples, case studies
4. Technical Description, architecture, internals
5. How is it used and installed, requirements and in what platforms does it run on
6. Demo
7. References
3 .1.
Background
NoSQL, Extensible Record Stores, Cassandra’s Parents
4 .NoSQL Systems
NoSQL or Not-Only-SQL systems: Next Generation Databases. The initial movement started in 2009
with the goal of creating modern, web-scale DBs. Currently, they exist more than 225 NoSQL
systems.
In general, they share the following features:
• Schema-free databases • BASE (instead of ACID)
• Easy replication support • Huge amount of data
• Simple API • Horizontally scalable
• Distributed
• Open Source
5 .Extensible Record Stores (or Wide Column Stores)
• Motivated by Google’s Big Table.
• Basic Data Model: Rows and Columns
• Basic Scalability Model: Rows and Columns are splitted into nodes.
• Rows: split across nodes through sharding on the primary key.
• Columns: distributed over multiple nodes by using ‘column groups’.
• Other systems that use this technology: Hypertable, HBase.
6 .Cassandra’s Parents - Amazon Dynamo
What is it?
A highly-available and scalable storage system used by Amazon to store and retrieve user shopping
charts and other core services. It pioneered the idea of eventual consistency. Key-Value Store.
How it works?
Allows read and write operations to continue even during network partitions and resolves update
conflicts using different conflict resolution mechanisms.
Sacrifices consistency for availability.
Allows customization to meet desired preference.
Consistent Hashing, Vector Clocks (not in Cassandra), Gossip Protocol, Hinted Handoff, Read Repair
7 .Cassandra’s Parents - Google Bigtable
What is it?
A high performance data storage system built on Google File System and other Google
technologies.
How it works?
Provides both structure and data distribution but relies on a distributed file system for
durability.
Richer data model from Dynamo. One key, many values. Fast sequential access.
Columnar, SSTable Storage, Append-only, Memtable, Compaction
8 .Cassandra’s Parents
What features does Cassandra use from Google’s BigTable?
1. Column Families
2. Memtables
3. SSTables
What features does Cassandra use from Amazon Dynamo?
1. Consistent hashing
2. Partitioning
3. Replication
10 .2.
Description and Comparisons
What Cassandra is and how it is compared with other similar systems
11 .Avinash Lakshman
• Inventor, Apache Cassandra
• Co-inventor, Amazon Dynamo
12 .Prashant Malik
• Inventor, Apache Cassandra
• Technical Leader, Facebook
15 .Definition
• A distributed NoSQL database system for managing large
amounts of structured data across many commodity servers,
while providing highly available service and no single point of
failure.
16 .Timeline with activities
• July 2008
Facebook released Cassandra as an open-source project
• March 2009
Cassandra became an Apache Incubator project
• 17th February 2010
Cassandra graduated to a top-level project
• 2012
University of Toronto researchers studying NoSQL systems concluded that “In
terms of scalability, there is a clear winner throughout our experiments”
• 2010-2015
New releases of Cassandra
17 .Strengths
• Linear scale performance
The ability to add nodes without failures leads to predictable increases in
performance
• Supports multiple languages
Python, C#/.NET, C++, Ruby, Java, Go, and many more…
• Operational and developmental simplicity
There are no complex software tiers to be managed, so administration duties are
greatly simplified.
• Ability to deploy across data centres
Cassandra can be deployed across multiple, geographically dispersed data centres
18 .Strengths (1)
• Cloud availability
Installations in cloud environments
• Peer to peer architecture
Cassandra follows a peer-to-peer architecture, instead of master-slave architecture
• Flexible data model
Supports modern data types with fast writes and reads
• Fault tolerance
Nodes that fail can easily be restored or replaced
• High Performance
Cassandra has demonstrated brilliant performance under large sets of data
19 .Strengths (2)
• ColumnFamily Store
Cassandra stores columns based on the column names, leading to very quick slicing
• Tunable consistency
Support for strong or eventual data consistency across a widely distributed cluster
• Schema-free/Schema-less
In Cassandra, columns can be created at your will within the rows. Cassandra data
model is also famously known as a schema-optional data model
• AP-CAP
Cassandra is typically classified as an AP system, meaning that availability and
partition tolerance are generally considered to be more important than consistency in
Cassandra
21 .Variable number of columns per row
22 .Weaknesses
Use Cases where is better to avoid using Cassandra
• If there are too many joins required to retrieve the data
• To store configuration data
• During compaction, things slow down and throughput degrades
• Basic things like aggregation operators are not supported
• Range queries on partition key are not supported
• If there are transactional data which require 100% consistency
• Cassandra can update and delete data but it is not designed to do so
23 .Business Insider
“The basic problem Cassandra solved is that when you have a lot of
data sitting on a lot of servers, as Facebook does, you end up with a
house of cards. A single server going down can collapse the whole
stack.”
24 .Cassandra compared to other
NoSQL Systems
25 .Read & Write latency for workload Read/Write
26 .Throughput for workload Read/Write &
Read/Scan/Write
27 .Insert-mostly Workload
28 .Mixed Operational & Analytical Workload
29 .Read-Modify-Write Workload
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