Database Reference
In-Depth Information
Understanding the architecture of
Cassandra
Cassandra is a relative latecomer in the distributed data-store war. It takes advantage of two
proven and closely similar data-store mechanisms, namely
Bigtable: A Distributed Storage
System for Structured Data
, 2006 (
http://static.googleusercontent.com/external_content/un-
trusted_dlcp/research.google.com/en//archive/bigtable-osdi06.pdf
)
and
Amazon Dynamo:
Amazon's Highly Available Key-value Store
, 2007 (
http://www.read.seas.harvard.edu/
~kohler/class/cs239-w08/decandia07dynamo.pdf
). The following diagram displays the read
throughputs that show linear scaling of Cassandra:
Like BigTable, it has a tabular data presentation. It is not tabular in the strictest sense. It is
rather a dictionary-like structure where each entry holds another sorted dictionary/map.
This model is more powerful than the usual key-value store and it is named a table,
formerly known as a column family. The properties such as eventual consistency and de-
centralization are taken from Dynamo.
We'll discuss column family in detail in a later chapter. For now, assume a column family is
a giant spreadsheet, such as MS Excel. But unlike spreadsheets, each row is identified by a
row key with a number (token), and unlike spreadsheets, each cell may have its own unique
