Abstract: From open source to self-research, those doorways in the database field.
When it comes to databases, open source is bound to be talked about.
But for a long period of time, taking relational database as an example, it has always been a patent held by commercial companies. The entire database market was monopolized by these big companies until the first open source version of MySQL appeared in the 1990s. Only now has the open source and open database market.
According to the latest database popularity rankings published by DB-Engines, in the top 10, only open source databases occupy 7 seats, including relational databases MySQL, Postgre SQL, non-relational databases MangoDB, Redis, Elasticsearch and Cassandra.
It is precisely because open source databases are so popular that more and more commercial companies are willing to do more in-depth optimization based on these open source databases.
Why self-research based on open source database?
Although open source databases do not have high commercial licensing fees, there are many problems with using open source databases, especially in the data-supported Internet era, it is impossible to handle various unexpected situations alone.
Many open source databases have poor ease of use and weak supporting capabilities, and require constant maintenance. Moreover, once data loss is encountered, it is difficult to recover quickly, and the loss caused is immeasurable. At the same time, open source databases also have to face various large and small cost expenditures such as servers, database maintenance and upgrades, and human operation and maintenance. It is difficult to meet the rapid expansion and sustainable development of business.
At this time, many cloud vendors will do some work for DBA operation and maintenance personnel once and for all, let open source databases go to the cloud, and take care of the "trivial" operation and maintenance work at the bottom.
Take Huawei Cloud RDS series products as an example. RDS for MySQL, RDS for PostgreSQL services, and DDS document database services (document type Mongo) are all database services based on open source, focusing on the most basic cloud native development requirements for cloud databases , It is mainly for business scenarios with small data scale and general performance requirements, and provides solutions with the ultimate cost-effectiveness.
However, the problem ensues. The open source database cloud can only solve the requirements of small and medium-sized enterprises such as simplified deployment, operation and maintenance, optimization, and extreme cost-effectiveness, but it cannot meet the requirements of finance, government and enterprises for data security, response speed, reliability, and availability. Large enterprises with strict requirements.
After weighing the pros and cons, many companies will choose the combination model of open source database + commercial database to ensure the availability and reliability of data.
The GaussDB series is a new generation of distributed database product series created by combining Huawei’s accumulated years of database research and development experience. Based on self-research and innovation, based on a unified architecture, on the one hand, it embraces and is compatible with ecosystems such as MySQL and Mongo. On the other hand, it creates an openGauss ecosystem. Facing government and enterprise customers, it emphasizes the demands of high performance, high reliability, and high security.
In terms of relational databases, Huawei Cloud officially released the cloud-native GaussDB (for MySQL) database in July this year. At the same time, the distributed database GaussDB (openGauss) based on the openGauss kernel of Huawei's open ecology will also be officially released for commercial use within the year.
In terms of non-relational databases, the focus is on building a cloud-native GaussDB NoSQL multi-mode database series that supports document type (Mongo), wide table type (Cassandra), time series (Influx), KV (Redis) and other multi-protocol interfaces. Currently, GaussDB (for Mongo), GaussDB (for Cassandra), and GaussDB (for Redis) have been launched.
Compared with open source databases, GaussDB series databases support NDP (near data process) technology, which allows calculation and data fusion, speeds up data processing, and greatly improves overall performance.
Take GaussDB (for MySQL) as an example. It is based on Huawei's latest generation of DFV distributed storage, adopts a separate computing and storage architecture, supports the rapid expansion of read-only nodes with 1 write and 15 reads, and supports up to 128 TB of mass storage, which can achieve more than one million Grade QPS throughput, single node performance is improved 7 times compared with native MySQL.
GaussDB NoSQL has strong multi-mode data management capabilities. It has made a qualitative leap compared to pure open source software in terms of concurrent read and write capabilities, expansion and expansion, failure reconstruction time, backup efficiency, and recovery efficiency.
The most important thing is that Huawei GaussDB database fully supports diversified computing power including Kunpeng and x86, and has E2E R&D capabilities from chips to servers, storage, operating systems, and databases, so it has a unique database software and hardware performance tuning. Advantages, such as the push-down storage of the GaussDB database DB operator, which in turn achieves a 30% improvement in performance compared to the partner database.
openGauss, to create a new open source database ecosystem
While actively embracing the existing open source database ecosystem, Huawei Cloud is also building an openGauss ecosystem.
openGauss is an open source relational database management system, issued under Mulan's loose license v2. Its core is derived from PostgreSQL, and it focuses on continuously building competitive features in the direction of architecture, transactions, storage engines, and optimizers. Deeply optimized on ARM architecture chips, and compatible with x86 architecture. Its technical characteristics are as follows:
Concurrency control technology based on multi-core architecture, NUMA-Aware storage engine, SQL-Bypass intelligent routing execution technology, release the processor's multi-core expansion capability, and achieve 1.5 million tpmC performance in two-channel Kunpeng 128-core scenarios;
Support fast failover with RTO<10S, full link data protection, meeting safety and reliability requirements;
Through intelligent parameter tuning, slow SQL diagnosis, multi-dimensional performance self-monitoring, online SQL time prediction and other capabilities, the operation and maintenance from complex to simple.
Huawei released the openGauss community version source code (https://opengauss.org) in June 2020, encouraging capable partners to launch openGauss-based databases to jointly prosper the database industry ecosystem.
Currently, Huawei Cloud has launched a commercial version of GaussDB (openGuass) based on the openGauss kernel and enhanced distributed capabilities, and more business partners will join in the future.
What needs to be emphasized is that openGauss is an open ecosystem: open architecture, open code, open technology and open communities. It will not allow the database ecosystem to move from a closed Oracle to another closed "new Oracle" just because it is promoted by Huawei. This method of openGauss allows more "comrades" to work together to solve defects, understand this architecture, and make maintenance more convenient.
For enterprises, only by choosing an open ecosystem can their business have better continuity. If you transform from a closed ecosystem to another closed ecosystem, the problem of business continuity is not essentially solved.
After all, an ecosystem that is not open has no vitality, especially database software.
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