NoSQL databases scale by adding more commodity servers. With more commodity servers come increased costs and complexities. Some NoSQL systems are better at this than others and need less. Continue reading Operations costs are the Achille’s heel of NoSQL
1. Do you know what your queries will look like ? In traditional SQL you design your data model to represent your business objects. Your queries can then evolve over time and can be ad-hoc. You can even create views, materialized or otherwise, to facilitate even more complex analytical queries. Cassandra does not offer the flexibility of traditional SQL. While your data model can … Continue reading Ten Questions to Consider Before Choosing Cassandra
Big Data is not Hadoop, and Hadoop is not Big Data. A lot of people are surprised that somehow Big Data adoption is growing while Hadoop is struggling. There is some speculation as to why and I have a much more pragmatic explanation: Hadoop is not SQL. Not all developers are created equal. Not all developers can pick up new skills – and enjoy doing … Continue reading Big Data is not all about Hadoop
Google recently launched Cloud BigTable – a cloud NoSQL service that is compatible with Apache HBase API. What this means is that an existing ecosystem of Hadoop applications is immediately binary-compatible with this new service and it doesn’t require any changes to the API. Google is not only marketing this as an alternative to Hadoop, but it is also marketing it as an alternative to … Continue reading We Need a Cloud Version of Cassandra
One thing I did not realize about Cassandra is that Apple is (or was) one of the biggest Cassandra users out there: Word in Goldmacher’s circles is that Apple will be “replacing” its huge Cassandra noSQL implementation with FoundationDB. Apple uses Cassandra for “iMessage, iTunes passwords, a bunch of stuff,” he says. In fact, Apple is touted as having one of the largest production deployments … Continue reading Apple is (or was) the Biggest User of Apache Cassandra
I’ve written before that Cassandra’s achilles’ heel is devops: Storage, redundancy and performance are expanded by adding more nodes. This can happen during normal business hours as long as consistency parameters are met. Same applies to node replacements. As the number of servers grows be prepared to hire a devops army or look for a managed solution. Datastax offering helps but still not enough. Even … Continue reading Ordered Sets and Logs in Cassandra vs SQL
In November last year I pointed out how tempted I was to replace Cassandra with DynamoDB. Since then I have done some research and things are not as straightforward as they may seem at first. I’d like to revisit my post and clarify a few things. On elasticity of Cassandra I said the following: Scaling a Cassandra cluster involves adding new nodes. Each additional node … Continue reading Trying to Replace Cassandra with DynamoDB ? Not so fast
