Jonathan Ellis:

More qualitatively but perhaps even more important, this addresses the paradox of choice we’ve had in the Cassandra Java world: multiple driver choices provide another barrier to newcomers, where each must evaluate the options for applicability to his project. Having just done such an evaluation to settle on Cassandra itself, this is the last thing they want to spend time on.

And that’s the best-case scenario. More often, a fragmented landscape leads to many solutions, each of which solve a different 80% of the problem. Better to have a single, well-thought-out solution, that lets people get started writing their application immediately.

This is the best argument ever for having official drivers.

✚ In the early days and over long time it’s quite difficult for a company to offer only official drivers. But there’s a solution for that too: recommend one. And support its maintainers.

Original title and link: Best argument for official drivers (NoSQL database©myNoSQL)

via: http://www.datastax.com/dev/blog/the-native-cql-java-driver-goes-ga

The Aurelius team describing an advanced benchmark of Titan, a massive scale property graph allowing real-time traversals and updates, sponsored by Pearson, developed and run over 5 months:

The 10 terabyte, 121 billion edge graph was loaded into the cluster in 1.48 days at a rate of approximately 1.2 million edges a second with 0 failed transactions. These numbers were possible due to new developments in Titan 0.3.0 whereby graph partitioning is achieved using a domain-basedbyte order partitioner.

✚ The answer to why Titan is built on Cassandra can be found in this interview between Aurelius CTO Matthias Broecheler and DataStax co-founder Matt Pfeil:

[…] we don’t have to worry about things like replication, backup, and snap shots because all of that stuff is handled by Cassandra. We really just focus on: “How do you distribute a graph?”, “How do you represent a graph efficiently in a big table model?”, “How do you do things like etched compression and other things that are very graph specific in order to make the database fast? And, lastly, “How do to build intelligence index structures so that the graphs traversals, which are the core of any graph database, so that those are as fast as possible?”

Original title and link: Titan: Data Loading and Transactional Benchmark (NoSQL database©myNoSQL)

via: http://www.planetcassandra.org/blog/post/educating-the-planet-with-pearson

Aleksey Yeschenko has an interesting post about the impact deletes can have on Cassandra and different workaround solutions:

Specifically, tombstones will bite you if you do lots of deletes (especially column-level deletes) and later perform slice queries on rows with a lot of tombstones.

I wouldn’t call this a “you got your data model wrong”, but rather a known implementation limitation that has impact on some scenarios in which a different data model should be used; the difference, while only semantic, is that the error is not on the user.

In other words, if you use column-level deletes (or expiring columns) heavily and also need to perform slice queries over that data, try grouping columns with close “expiration date” together and getting rid of them in a single move.

Original title and link: Cassandra anti-patterns: Queues and queue-like datasets or when Deletes can bite (NoSQL database©myNoSQL)

via: http://www.datastax.com/dev/blog/cassandra-anti-patterns-queues-and-queue-like-datasets

Ben Bromhead (instaclustr) for High Scalability:

To determine the suitability of a provider, your first port of call is to benchmark. Choosing a service provider is often done in a number of stages. First is to shortlist providers based on capabilities and claimed performance, ruling out those that do not meet your application requirements. Second is to look for benchmarks conducted by third parties, if any. The final stage is to benchmark the service yourself.

✚ Peter Bailis asks a very valid question: if it’s the default YCSB and it’s a benchmark, where are the results?”

✚ instaclustr offers a totally managed hosting solution for Cassandra. (Disclaimer: they’ve sponsored myNoSQL in the past)

Original title and link: 5 Steps to Benchmarking Managed NoSQL - DynamoDB Vs Cassandra (NoSQL database©myNoSQL)

via: http://highscalability.com/blog/2013/4/3/5-steps-to-benchmarking-managed-nosql-dynamodb-vs-cassandra.html

Sam Tunnicliffe’s describes the old and new, optimized behavior of secondary indexes writes in Cassandra 1.2:

While secondary indexes can add a lot of flexibility to the way data is modelled and accessed, they do add complexity on the server side as the indexes need to be kept in sync with the primary data. Until recently, this has led to some significant trade offs in write throughput and IO utilisation as we always had to perform a read before the write in order to update any relevant secondary indexes. In Cassandra 1.2, this area has been substantially reworked to remove the need for read-before-write. New index entries are now written at the same time as the primary data is updated and old entries removed lazily at query time. Overall, this has lead to some decent performance improvements.

Original title and link: Improving Secondary Index Write Performance in Cassandra 1.2 (NoSQL database©myNoSQL)

via: http://www.datastax.com/dev/blog/improving-secondary-index-write-performance-in-1-2

This RSS reader app from Netflix can be a very good excuse to use Cassandra, some of the open source projects from Netflix and why not create an alternative to Google’s Reader which is declared defunct or alive every couple of months:

Projects you’ll use: Cassandra with Astyanax, Archaius, Blitz4j, Eurka, Governator, Hystrix, Karyon, Ribbon, Servo. As for myself, I’ve already checked out the code.

Original title and link: RSS Reader With Cassandra and Netflix OSS Tools (NoSQL database©myNoSQL)

via: http://techblog.netflix.com/2013/03/introducing-first-netflixoss-recipe-rss.html

Robin Schumacher describes the new security features added to Apache Cassandra and DataStax Enterprise:

This article will concentrate on the new internal authentication and authorization (or permission management) features that are part of both open source Cassandra as well as DataStax Enterprise. Authentication deals with validating incoming user connections to a database cluster, whereas authorization concerns itself with what a logged in user can do inside a database.

I’m happy to see NoSQL databases entering the space of security as this would ease their way inside enterprises. But I fear a bit the moment when the marketing message will change from “it’s too early to provide security features” to “the first enterprise grade NoSQL database”.

Original title and link: A Quick Tour of Internal Authentication and Authorization Security in DataStax Enterprise and Apache Cassandra (NoSQL database©myNoSQL)

via: http://www.planetcassandra.org/blog/post/a-quick-tour-of-internal-authentication-and-authorization-security-in-datastax-enterprise-and-apache-cassandra