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MariaDB ColumnStore Upcoming Release Announced

MariaDB® Corporation, the recognized leader in open-source databases, announced the upcoming release of its big data analytics engine, MariaDB ColumnStore.

Tahseen Jamil Apr 06, 2016

MariaDB® Corporation, the recognized leader in open-source databases, announced the upcoming release of its big data analytics engine, MariaDB ColumnStore.
The company states,
“The release is the industry’s first to enable transactional and massively parallelized analytic workloads under the same roof. This unification is possible because of MariaDB’s extensible architecture that allows simultaneous use of purpose built storage engines for maximum performance, simplification, and cost savings, an approach which stands apart from competitors like Oracle, and obviates the need to buy and deploy traditional columnar database appliances.”
Will Powers, Director Systems Infrastructure and Data Services at Bandwidth, states,
“Columnar database technology is central to our ability to give customers the insights they need to grow their revenue and protect them from fraud. We are extremely happy to see MariaDB take it up, as there are truly no alternatives that can match the combination of low operating cost and exceptional performance at scale.
Powers goes on to add,
“We have been a hybrid MySQL and MariaDB shop, but are standardizing on MariaDB for future development. MariaDB’s new analytical processing and security advances are of urgent importance to our business, and I’m looking forward to continued rapid innovation from MariaDB and its open-source community.”
Michael Howard, CEO of MariaDB, comments,
“I’ve seen first-hand how traditional columnar appliances arose as reactions to the cost and complexity of Oracle. But these reactions have only increased complexity and cost further, and most importantly, over-looked critical features. In contrast, MariaDB ColumnStore is ACID compliant, blazingly fast, massively parallelized, and uses a distributed storage engine. What’s equally important is its front end--MariaDB, which provides the same interface, same security, same SQL richness simplifying management, reducing operating costs."
MariaDB ColumnStore is a columnar storage engine for massively parallel distributed query execution and data loading, It supports a huge spectrum of use cases which includes real-time, batch and algorithm. It easily performs complex aggregation, joins, and windowing functions at the data storage level in order to increase performance. MariaDB ColumnStore is Open Source GPL2, a fork based on InfiniDB and open source community contributions.
The company has also announced new data streaming capability in MariaDB MaxScale which will simplify real-time data propagation to external Data Lakes or Data Warehouses. The new features allow transactions in MariaDB to be replicated in real time to Hadoop or any other data store. It also enables MaxScale and MariaDB to be configured in order to handle replication in mission critical applications, without the need to impact the performance, and it also includes all the essential metadata so that any program can easily read it with no pre-value overhead.
Michael “Monty” Widenius, MariaDB’s CTO, states,
“Big data analytics is a priority for businesses that need to scale their analytics capabilities and extract greater value from growing data volumes. MariaDB ColumnStore and MariaDB MaxScale with data streaming provide a holistic approach to increasingly demanding analytical processing tasks. Our approach is aimed at any company who does not want to pay big for big data. For the MariaDB/MySQL community, MariaDB ColumnStore is the first complete data warehouse solution. We believe our engineering team and community have built a new generation database platform for the modern data-driven business.”

Tahseen Jamil
Tahseen Jamil

I am a freelance writer for the past 3 and half years. I aspire to generate interesting and productive ideas to the readers through my writing. My objective is to share information with the readers and inform them about ... Read more

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