The Cassandra architecture is unique and is the main reason for its ability to outperform. When we say linear scalability, it means that there is no master-salve legacy. All the nodes play an identical role and communicate with each other equally. In this way, Apache Cassandra becomes the right choice for handling large chunks of data or user operations across multiple data centres. This homogeneous node system helps Cassandra provide continuous availability and up time.
Features of Apache Cassandra
Many companies such as Apple, Netflix, eBay, Instagram etc have successfully deployed and benefited from Apache Cassandra. Some of the features are mentioned below:
With the cluster of homogeneous nodes, the data is automatically replicated multiple times to avoid any fault tolerance. It also supports replication of data across multiple data centres.
New users and hardware can be easily added linearly on to Apache Cassandra without any issues of downtime or any interference to the already running applications.
Cassandra demonstrates high linear scale performance. It maintains a quick response time even when you add new nodes to the homogeneous network.
The architecture of Cassandra which allows all the nodes to communicate simultaneously at the same level ensures that there is no single point of failure and hence it is continuously available for critical business functions. The decentralized network of identical nodes ensures that there are no network bottlenecks.
Cassandra is a highly suitable for applications where data is critical and when business can’t afford to lose data or even encounter a downtime in the data center. It accommodates all possible data formats and allows you to change data structures as required.
We offer full lifecycle of Big Data services including POC, architectural consulting, data modelling, automation and preventive maintenance.
1- Cassandra installation and configuration.
We provide development, consulting and training services on Apache and DataStax Enterprise Cassandra, including strategic planning & roadmap, data migration, and implementation of Cassandra in the data system. With our services, adding up data from multi-locations at high-speed comes handy.
2- Setting up and configuring a cluster with replication.
3- Application development using Cassandra as a data storage
4- Cassandra consulting: analyzing your business aand migrating parts of your application schema to Cassandra to improve performance.
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b- 10+ Vendor-independent benchmarks featured in CIO.com, NetworkWorld, ComputerWorld. These benchmarks help software architects and DBAs to find performance bottlenecks and fine-tune their NoSQL-based systems.
c- Access to 250+ in-house front-end, big data, Ruby, .NET, Java, and QA engineers—we cover the entire application development life cycle.
d- A big data development team of 30+ engineers with proven expertise in implementing NoSQL data stores.
The popularity of NoSQL databases (especially Cassandra) has been increasing day by day. Now, as we are developing Cassandra applications, we may need new tools to monitor database performance efficiently. Our Developers have difficulty optimizing something they can't see. When problems related to performance occur and proper analysis is needed, the statistical data generated by monitoring tool will be of a lot help. To optimize NoSQL applications, our developers need to have an idea about how the database is behaving in different working scenarios.
Here we are using some command line tools provoded by Apache and those are listed below.
1- cqlsh:-the CQL shell
cqlsh is a command line shell for interacting with Cassandra through CQL (the Cassandra Query Language). It is shipped with every Cassandra package, and can be found in the bin/ directory alongside the cassandra executable. cqlsh utilizes the Python native protocol driver, and connects to the single node specified on the command line.
The nodetool utility (nodeprobe in versions prior to 0.6) provides a simple command line interface to these exposed operations and attributes.
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