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MariaDB Labs: Research Division That Tackles Challenges in Database Field

To make discoveries that spawn new use cases

MariaDB Corporation announced the creation of MariaDB Labs, a research division that tackles the challenges in the database field.

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Aimed at pioneering breakthroughs, MariaDB Labs will bring together experts and leaders to make discoveries that spawn new use cases. For its inaugural initiative, MariaDB Labs will collaborate with Intel Corp. to implement a reference architecture for databases with disaggregated memory and storage in modern data centers.

Geo-distributed applications, non-volatile memory, predictive optimizers and self-driving databases are the new inflection points in this era of modern data computing,” said Michael Howard, CEO, MariaDB, “With MariaDB Labs, we want to recharge the conversation and inspire new research in solving these challenges. The first initiative under this goal is our collaboration with Intel on a new reference architecture and implementation based on distributed storage using high-performance fabrics.

It is focused on three areas of research, including:

  • Machine learning to transform the ways in which the company is deployed and managed in public and private clouds, and employ learning methods for database self-configuration and self-optimization.

  • Distributed computing to break through long-held beliefs in relational technology and compromises in NoSQL, raising the bar for web-scale, geo-distributed deployments and executing on new approaches for one of the industry’s most difficult to solve problems.

  • Next-generation chips, memory and storage to change the infrastructure on which databases run, advancing performance, HA, costs and energy conservation.

Traditional databases are facing new and challenging requirements emerging from cross-platform cloud deployments to elastic scale-out to global demands for HA, to name a few,” said Roger Bamford, board advisor, MariaDB Labs. “Solving for these will be difficult and is truly groundbreaking work. The impact will be significant, not only to remove barriers but to open the door for new opportunities and use cases.

MariaDB Labs and Intel Innovate on cloud-centric shared storage architecture
As businesses become more data intensive, cost per transaction is an important metric in keeping costs in line. At the same time, companies are increasingly looking to cut ties with proprietary solutions in favor of cloud-friendly, open source platforms that can be readily integrated into data environments. For the inaugural MariaDB Labs initiative, Intel and MariaDB are collaborating on an open source database using a disaggregated cloud-centric storage architecture. The research will specifically examine the use of shared, log-structured storage to support the persistence requirements of distributed databases, bringing fast recovery and cloning through an automated recovery process.

In addition, this reference architecture extends the MyRocks storage engine in MariaDB, optimized for SSDs for better compression, faster replication and data loading. The architecture is designed with the Xeon Scalable platform, Optane SSDs and Intel Persistent Memory. The company expects customers will see increased performance, increased scale per server and support for bigger, more affordable data sets.

Our research collaboration with MariaDB will focus on an innovative distributed log architecture using Intel Optane SSDs and Intel Persistent Memory woven together through high-performance fabrics,” said Alper Ilkbahar, VP, data center croup GM, datacenter memory and storage solutions, Intel. “Our shared goal is to enable faster recovery and cloning, increase overall performance and resilience, and reduce solution TCO from today’s level.

Intel was discussing the details of this approach and early results during MariaDB’s M|18 user conference in a session titled Intel and MariaDB: Strategic collaboration to enhance MariaDB functionality, performance and TCO.

Resources:
MariaDB M|18 keynotes live
Read MariaDB M|18 conference highlights

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