cassandra vs rdbms

Summary There are many limitations to CQL compared to SQL because Cassandra is designed for large data storage, and its deployment patterns are based on partitioning, unlike MONGO and replica sets, a small database cluster design that is fragmented when data is large. To provide retrieval efficiency, the CQL syntax is limited to avoid inefficient query statements. The Cassandra data is distributed to each

Here we start to use Java to operate the Cassandra database, not limited to client operations. For operations on the client Cassandra-CLI and nodetool, you can use the help command on the command line to get a lot of help. I am using thrift to operate databases. This is a relatively low-level method that uses the most basic API directly. Although there are more advanced methods to operate, it is still neces

Summary This paper mainly introduces the index in Cassandra, materialized view, some knowledge points need to have a basic understanding of Cassandra to understand. such as how the data is distributed in the Cassandra node. If there is something you don't understand, you can read the article before this column. or send me an email and discuss cnstonefang@gmail.c

1. Inverse entropyThe Cassandra database draws on Amazon's Dynamo in a distributed architecture, and references Google's bigtable on the data storage model. So in the data consistency and dynamo and BigTable have a deep connection, inverse entropy mechanism is a manifestation of this connection. inverse entropy, like the gossip protocol, is an algorithm based on infectious disease theory, which is mainly used to ensure that data on different n

Recently installed Cassandra to the product server, a lot of things require a lot of strict, such as Perf used in the JMX, previously as long as the IP can access, but the product server is not, so there is a security risk, nodetool-h host can add and delete nodes. So the thing to talk about today is Cassandra JMX's authorization and access control. Here is the first, the most common use of passwords and a

previous article Cassandra The Getting Started guide, we've configured a single node cluster, and then we'll add a few more nodes to the cluster to see how multiple nodes work at the same time.The exchange of information between Cassandra nodes is through a mechanism called gossip (which is not known for a moment to be appropriate for which proper noun to translate). But to get a message to a newly added no

This week, I took over the maintenance of a Cassandra system. One of them was to import the data of the application to the Cassandra cluster we maintained and provide HTTP access services for the application. This is my first time in contact with the kV system. It turns out that I have seen kV and nosql. But there is actually no practical experience. After two days of learning and taking over, I finally fig

In the previous articleArticleUsing Binary memtable to import large amounts of data into cassandra explains how to use binary memtable to import large amounts of data into Cassandra. This week, we have been watching if we use binary memtable to import a large amount of data. Today, I still think this version is not suitable for importing data. The reason is as follows: In0.6 +Version,CassandraCl

A preface　　In the previous article, I briefly described the installation and launch of Cassandra on the Windows platform, and described the basic data model of Cassandra in a bottom-up perspective. Before I learn a new thing, I think the best way to do this is to get to the macro and start with the details. This article analyzes the Cassandra data model from a to

includes Spark, Mesos, Akka, Cassandra, and Kafka, with the following features: Contains lightweight toolkits that are widely used in big data processing scenarios Powerful community support with open source software that is well-tested and widely used Ensures scalability and data backup at low latency. A unified cluster management platform to manage diverse, different load applications. When deploying specific applications,

includes Spark, Mesos, Akka, Cassandra, and Kafka, with the following features: Contains lightweight toolkits that are widely used in big data processing scenarios Powerful community support with open source software that is well-tested and widely used Ensures scalability and data backup at low latency. A unified cluster management platform to manage diverse, different load applications. When deploying specific applications,