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With the upcoming Cassandra 4.0 release, there is a lot to look forward to. Most excitingly, and following a refreshing realignment of the Open Source community around Cassandra, the next release promises to focus on fundamentals: stability, repair, observability, performance and scaling.
We must set this against the fact that Cassandra ranks pretty highly in the Stack Overflow most dreaded databases list and the reality that Cassandra is expensive to configure, operate and maintain. Finding people who have the prerequisite skills to do so is challenging.
August 8, 2017 | Cassandra
Recently, the sad news has emerged that Basho, which developed the Riak distributed database, has gone into receivership. This would appear to present a problem for those who have adopted the commercial version of the Riak database (Riak KV) supported by Basho.
This blog is written exclusively by the OpenCredo team. We do not accept external contributions.
My recent blogpost I explored a few cases where using Cassandra and Spark together can be useful. My focus was on the functional behaviour of such a stack and what you need to do as a developer to interact with it. However, it did not describe any details about the infrastructure setup that is capable of running such Spark code or any deployment considerations. In this post, I will explore this in more detail and show some practical advice in how to deploy Spark and Apache Cassandra.
In recent years, Cassandra has become one of the most widely used NoSQL databases: many of our clients use Cassandra for a variety of different purposes. This is no accident as it is a great datastore with nice scalability and performance characteristics.
However, adopting Cassandra as a single, one size fits all database has several downsides. The partitioned/distributed data storage model makes it difficult (and often very inefficient) to do certain types of queries or data analytics that are much more straightforward in a relational database.
February 16, 2017 | Cassandra
One of the default Cassandra strategies to deal with more sophisticated queries is to create CQL tables that contain the data in a structure that matches the query itself (denormalization). Cassandra 3.0 introduces a new CQL feature, Materialized Views which captures this concept as a first-class construct.
If there is one thing to understand about Cassandra, it is the fact that it is optimised for writes. In Cassandra everything is a write including logical deletion of data which results in tombstones – special deletion records. We have noticed that lack of understanding of tombstones is often the root cause of production issues our clients experience with Cassandra. We have decided to share a compilation of the most common problems with Cassandra tombstones and some practical advice on solving them.
September 15, 2016 | Cassandra
Cassandra isn’t a relational database management system, but it has some features that make it look a bit like one. Chief among these is CQL, a query language with an SQL-like syntax. CQL isn’t a bad thing in itself – in fact it’s very convenient – but it can be misleading since it gives developers the illusion that they are working with a familiar data model, when things are really very different under the hood.
September 6, 2016 | Cassandra
A growing number of clients are asking OpenCredo for help with using Apache Cassandra and solving specific problems they encounter. Clients have different use cases, requirements, implementation and teams but experience similar issues. We have noticed that Cassandra data modelling problems are the most consistent cause of Cassandra failing to meet their expectations. Data modelling is one of the most complex areas of using Cassandra and has many considerations.
August 24, 2016 | Cassandra
At OpenCredo we are seeing an increase in adoption of Apache Cassandra as a leading NoSQL database for managing large data volumes, but we have also seen many clients experiencing difficulty converting their high expectations into operational Cassandra performance. Here we present a high-level technical overview of the major strengths and limitations of Cassandra that we have observed over the last few years while helping our clients resolve the real-world issues that they have experienced.
January 6, 2014 | Cassandra
The team over at Cucumber Pro recently posted a sneak peek on their blog, demonstrating some key features of their offering.
As more of a technical user of Cucumber, there isn’t much that’s new or ground-breaking for me – almost every feature is already available through your preferred IDE combined with a few plugins.
December 2, 2013 | Cassandra
Perhaps the most important of Cassandra’s selling points is its completely distributed architecture and its ability to easily extend the cluster with virtually any number of nodes. Implementing a classical RDBMS-style transaction consisting of “put locks on the database, modify the data, then commit the transaction”-style operations are simply not feasible in such an architecture (i.e. that doesn’t scale well).