HANGZHOU, China, May 31, 2022 /PRNewswire/ --On May 16th, 2022, LDBC-SNB released the newest audit test performance record set by Galaxybase, a high performance distributed graph database developed by CreateLink Technology. Galaxybase scored a soaring 70% improvement in throughput, and over 600% increase in average query performance over the previous record, along with rigid tests on system stability, availability, result correctness, transactional support, and recoverability.

The test was performed by an independent and impartial third-party auditor appointed by LDBC on standard cloud environment. The preparation of the test environment, data generation, data loading, test execution, and the correctness verification of test results all strictly complied with LDBC-SNB specifications. To further ensure the credibility and validity of the test results, LDBC conducted a detailed audit of the test code, the entire test environment, and test process. A full disclosure report is publicly available for downloadon the LDBC homepage.

Dr. Chen ZHANG, Founder and CEO of CreateLink Technology, will give a keynote speech titled "New LDBC SNB benchmark record by Galaxybase: More than 6 times faster and 70% higher throughput" to share the audit details at 2022 ACM SIGMOD/PODS International Conference on Management of Data on June 17 2022, 11 am EDT, 23 pm BST. (click to view online)

About LDBC and SNB test

Linked Data Benchmark Council (LDBC) is a globally recognized organization for graph database benchmark standards and audit test. It brings together the world's leading industrial hardware and software giants such as Intel, Oracle, as well as experts and scholars from higher education institutions. LDBC aims to develop fair, honest, and comparable methods and mechanisms to measure graph database management systems and promote the development of this cutting-edge technology across the globe, together with its member organizations.

Social Network Benchmark (SNB) is one of the benchmark suites developed by LDBC. The benchmark suite consists of two distinct workloads on common data set Interactive workload and Business Intelligence (BI) workload, corresponding to test sets that measure the performance of graph data in interactive queries and business intelligence queries respectively. Compared with standalone test cases with simple metrics, LDBC-SNB is not only more similar with complex real-world business query scenarios, but also imposes higher requirements on the concurrent execution and transaction processing capability of graph database systems.

About the test details

The competed audit test was LDBC_SNB Interactive workload. Galaxybase successfully completed the audit test with verified system configuration conformance to the description of the benchmark and its strict requirements involving result correctness, transaction support, system recoverability, zero-timeouts, high throughput, and low response time, etc. In particular, Galaxybase ACID test has researched serializable isolation level, which is stricter than the read committed isolation level required by the SNB Interactive specification. Additionally, Galaxybase passed the recoverability and durability validation test, in which the system was shut down and rebooted when the continuous benchmark test execution has reached 2 hours, and the data of the last successfully inserted record in the LDBC log remained intact and durable in the graph database.

In the performance test, Galaxybase used 48 clients to send out concurrent queries to stress test the system. The result showed zero timeout which is far below LDBC-SNB'sno-more-than-5% timeout requirement. With all official audit requirements fulfilled, Galaxybase outperformed LDBC's previous record (held by TuGraph) for all three datasets, namely 30G (80 million vertices, 500 million edges), 100G (270 million vertices, 1.7 billion edges), and 300G (800 million vertices, 5.3 billion edges), with 70% higher throughput and on average morethan 6 times faster query performance.The mean response time, the P50, P90, P95, and P99 response time of Galaxybase all shows better results than the previous record-holder. In particular, the best mean response time is more than 41 times faster, and the best P90 response time is more than 72 times faster.

No matter on queries of different data scale factors under the same test tasks or on queries of different complexity for different test tasks, Galaxybase all performed better. The larger the size of the datasets, the higher the differentiation, which fully demonstrates the excellent capability of Galaxybase to support large-scale data processing tasks.

Table 1: Summary of Galaxybase test results for different scale factors

Scale factor

Benchmark duration

Benchmark operations

Throughput

Query on-time compliance

SF-30

2h 14m 35.740s

74900196

9285.86operations/second

100.00%

SF-100

2h 05m 26.944s

63988107

8501.21

operations/second

100.00%

SF-300

2h 07m 24.645s

63989669

8370.52operations/second

100.00%

Remarks: SF-30, SF-100 and SF-300 correspond to the original dataset size of 30 G, 100 G and 300 G respectively.

Galaxybase can support both online transaction processing (OLTP) and online analytical processing (OLAP), according to Yan ZHOU, CTO of CreateLink. Compared with other graph databases, Galaxybase demonstrates lower response time, higher throughput, and higher horizontal scalability, making it the ideal choice for high performance graph database on large dataset, under the increasing demand for real-time analytics over massively connected enterprise data,.

Galaxybase is written with Java and C++. It takes full advantage of the runtime performance and memory control with C++ and the coding efficiency and easiness of troubleshooting with Java in the development of complex and reliable systems. In terms of storage system design, Galaxybase uses an innovative proprietary native graph datastore with customized optimization for index-free adjacency of graph data, enabling vertex-edge queries to be completed in an extremely efficient manner. The core datastore engine does not rely on any third-party open-source components, allowing the system to better optimizes graph queries and graph computation in concert with the underlying storage layer. In the query execution layer, Galaxybase is able to efficiently organize memory data through its proprietary memory allocation and management mechanism, while significantly reducing the JVM's GC time by using off-heap memory. Galaxybase provides a parallel iterative graph traversal approach, that uses multi-version control to reduce lock contention. This approach adaptively allocates the number of threads for parallel iterations based on the number of neighbours during neighbour iteration to achieve best utilization of system resources.

Galaxybase provides a rich set of query interfaces and programming APIs, such as Java, Python, Golang, etc.. It also has full support for the descriptive OpenCypher query language. For the audit test, Galaxybase completed the durability test using OpenCypher. For scenarios that require high system resource consumption and execution performance, Galaxybase also provides PAR (Parameterized Algorithm Routine) API that allows users to implement customized procedures and functions running on the server-side through Java code to gain better control over the query execution process and pursue extreme performance.

About CreateLink

Founded in 2016, CreateLink Technology has become the leading graph database software vendor in China. Its product Galaxybase is a native distributed parallel graph platform that has superior performance on complex graph queries and algorithms. Earlier this year, together with a team of experts from Sun Yat-sen University, Galaxybase nailed the intelligent graph mining challenge of 5 trillion relationship graph while maintaining security, performance, availability, and data integrity, easily breaking the once-challenging scale barrier with trillion+ relationship graph.

CreateLink is actively promoting graph technology across different industries with a diversity of application scenarios. Up to now, Galaxybase has served many leading customers in finance, energy, and Internet sectors, with successful applications in AML, fraud detection, power grid optimization, IT operation monitoring and maintenance as well as other complex real-time decision-making scenarios, empowering its customers to release the value of big data by connecting the dots.

To check LDBC-SNB test report and get more details of the report, please visit the Galaxybase website.

SOURCE Galaxybase

Continued here:

Galaxybase Breaks the Linked Data Benchmark Council (LDBC) Social Network Benchmark (SNB) Audit Test Record with Top-notch Performance - PR Newswire

Todays mining companies are complex organizations that operate in dynamic and evolving business environments.

To manage a successful mining operation involves navigating the diverse and increasingly complex challenges of sustainability, governance, and stakeholder engagement on top of the requirements of managing finances, inventories, and supply chains that are common to all operators.

Illumiti, a leading Canadian-based systems integration and management consulting company, is helping mining companies improve their business operations by implementing a cost-effective solution to enterprise resource planning (ERP) based on SAP software and then tailoring it to the individual needs of the company.

For most mining companies, their core processes, such as finance, procurement, and maintenance are to a large degree the same no matter where they operate, says Rory Friedman, Illumitis vice-president of mining.

He says that by digitizing a companys core business processes, Illumiti harnesses the power of the cloud and the basic functions of an ERP to help them improve cost control and make better decisions, which can lead to efficiency gains, growth in revenues, and a more empowered workforce.

By leveraging industry best practices, Illumiti implements the system as quickly and responsibly as possible, Friedman explains. When we first engage with a company, they often fall into the trap of believing that they need to create a perfect system with all the bells and whistles attached.

However, this approach, he says, can be often very costly and time-consuming, alienating those tasked with implementing and adopting the system, and can take years before the benefits and value of the system to the company are realized.

Our platform can often be implemented in just a few months, accelerating the time to value for shareholders while also providing visibility to key stakeholders involved in the process, which helps to create buy-in from those who are critical to its successful implementation and deployment.

To achieve this, Illumiti utilizes a modular template with the critical processes common to all mining operations, says Friedman.

Rather than re-inventing the wheel every time, our solution is 80% pre-built, which allows the company to focus on the other 20%, and so provides them with a platform that continuously improves over time and evolves with their business and the diverse and changing demands constantly placed on them.

Illumitis modular implementation approach is gaining considerable traction across the mining industry. The company has already helped more than 30 mining companies operating globally to reap the benefits of a faster, more efficient digitization of their business processes.

We generally introduce the ERP platform and protocols as early as the post feasibility study, before construction begins, Friedman says. The modular nature of the template means that the capabilities needed earliest are implemented at the start of the process, with additional capabilities added later as the mining operation matures.

He adds that by the time the mining operation goes into production, all the core modules are already in place and are tailored to the business's specific needs.

Although each companys situation is unique, with their business model, operations, and the markets they serve all determining their specific needs, Friedman compares implementing an ERP framework to building a house.

The platform can be seen as the plumbing or electricals or all the other common elements of the house's foundations. Once these foundations are in place, the owners can then focus on bringing their furnishings to personalize the space.

In the same way, he says, Illumitis rapid implementation and integration of its ERP allows its core business processes to be quickly digitized, allowing the company to identify opportunities for improvements to these processes.

Eliminating errors introduced during manual data entry, for example, frees up managers and supervisors to focus more on analyzing data and problem solving as they can take a more holistic approach to an operation, with the data collection and compilation left to the software, Friedman says.

He adds that, following implementation, the platform helps improve communications between different business functions such as finance, procurement, maintenance, and inventory management, which can lead to smoother and more effective interactions between stakeholders across a business and the streamlining of operations.

According to Friedman, process automation and advanced technologies like machine learning and artificial intelligence can be leveraged in various business functions like maintenance to drive material improvements by introducing predictive maintenance capabilities.

He says invoices, for example, can be scanned and then rapidly and accurately compared with goods or services received, which optimizes the system via automation, freeing up time to focus on analyzing data and identifying discrepancies instead of spending time entering data manually.

He adds that because all the data is contained in one system, retrieving vital information to help in understanding the cause of a problem becomes much quicker and simpler, saving the company time and money.

Illumitis ERP platform provides a mining company with the tools to help improve how the business operates instead of just operating the business, Friedman says.

The preceding Joint Venture Article is PROMOTED CONTENT sponsored by ILLUMITI and produced in co-operation with The Northern Miner. Visit http://www.illumiti.com for more information.

Original post:

JV Article: Illumiti helps mining companies reap the benefits of digitization - Canadian Mining Journal

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Register today!

Privacy. You would be hard-pressed to find a word used as frequently or with as much weight in recent years. As the world hurtles towards an increasingly digital future, concerns over data privacy have reached a fever pitch.

From high-profile cases of data breaches to tales of government surveillance, it seems that scarcely a day goes by without another story about how our personal information is being mishandled.

The digital age has brought with it many amazing advances, but it has also created new threats to our privacy. One of the biggest dangers comes from the way that big tech companies collect and use our data.

Most people are now familiar with the term data mining the process by which companies collect large amounts of data about our online activity and use it to target ads and sell products. But data mining is just the tip of the iceberg. Many tech companies are now using sophisticated methods to track our every move, both online and offline.

This tracking is made possible by the proliferation of devices that are connected to the internet. These devices collect a wealth of data about our whereabouts, our behaviors and even our physiology. This data is then used to create detailed profiles of each individual user.

These profiles are extremely valuable to companies, who use them to target ads, sell products and influence our behavior. In other words, they use our personal information to make money.

This business model has come under fire in recent years, as more and more people have become aware of the ways that their personal data is being used without their consent.

So what can be done to protect our privacy in the age of big tech? There are no easy answers, but there are some steps that we can take to help ensure that our privacy is not violated.

The answer is not merely a matter of public policy but an overall paradigm shift in the way we think about privacy. This would of course involve:

This last point goes back to the original intent of the internet. As a matter of fact, the internet was designed to be a decentralized network, where each user could connect to any other user without going through a central server. This design was based on the belief that decentralization would make the internet more resistant to censorship.

Unfortunately, this vision has not been realized. Instead, we have seen the rise of a small number of giant tech companies that now control most of the internet. These companies use their power to censor and manipulate the information that we see, and they collect vast amounts of data about our online activity.

This centralization of power is dangerous for democracy and privacy. It gives these companies too much control over our lives, and it makes it easy for them to violate our rights.

We need to build a new internet that is decentralized and democratized. This new internet should be designed to protect our privacy and promote free speech. It should give power back to the people, and it should be resistant to censorship and control.

The first step in building this new internet is to create decentralized alternatives to the centralized services that we use today. These alternatives will be built on the principles of privacy, security and freedom.

Privacy is a complex issue, and there is no one-size-fits-all solution. But by taking some simple steps to protect our privacy, we can make a difference. We can make sure that our data is not used to violate our rights, and we can help build a new internet that is free from censorship and control.

Daniel Saito is CEO and cofounder of StrongNode.

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For May's Asian Heritage Month in Canada, two historians in B.C.'s Interior are remembering the legacies of two early Chinese Canadian miners.

For more than a decade, Lorna Townsend in Quesnel and Richard Wright in Kamloops have bothstudied the history of Ah Bau and Chew Nam Sing, two of the most well-known pioneers among anestimated 5,000 people who came from Chinato B.C.'sCariboo region in the late 19th century to prospect for gold.

The Cariboo Gold Rush from 1861 to 1867 attracted thousands of prospectors from other parts of Canada, Britain, the United States, Latin America and China. The Royal B.C. Museum says many Chinese prospectors chose to make the Cariboo their new home and ran farms, grocery stores and other businesses to serve local communities.

Townsend, who volunteers with the Quesnel and District Museum and Archives, saidbased on her interpretation of census data, mining records and newspaper articles, Ah Bauwas born around 1840 in China, and started mining in the North Cariboo as early as 1862 in what is known today as the Ahbau Creek watershed between Quesnel and Hixon.

Ahbau Lake, Ahbau Creek Falls and Ahbau Creek Bridge are other places north of Quesnel that are named after the gold miner. There's also Ahbau Street in Prince George, about three kilometres west of the city hall.

Townsend saidshe doesn't know why the Prince George street is named after Ah Bau, but surmises people associate the lake and creek with him solely because he claimed and lived in the isolated 50,000-hectare watershed area for decades.

"There weren't a lot of people living in that area, and he spent 40 years there," she said. "I think the pioneers at the time would have associated that area with the man during those years, and so that was just perpetuated after his death."

Townsend saidAh Bau died in the spring of 1902 at his cabin located near Ahbau Lake. He was in his early60s.

She saidduring his heyday from 1864 to 1876, Ah Bau managed a team of 700 Chinese labourers to extract more than a million ounces of gold from the fields he claimed. She describes him as a "versatile" worker who also trapped for fur in winters, and served as a river pilot, steersman and a chef for merchants in the Peace River region.

Townsend saidAh Bau befriended mostly Indigenous men and those of European descent, who all loved him as a big-hearted, cheerful man.

"He would have died a very wealthy man, if not for his generosity he was always helping other people, and he also had a penchant for poker and whisky, so he often lost a lot of money," she said.

The Quesnel Museum says Chew Nam Sing, born in 1835 in China, spent some time mining gold in California before arriving in B.C. in 1858. Up until the 1870s, he bought up land on both sides of the Fraser River several kilometres north of Quesnel to raise livestock and grow vegetable cropswith his wife and children.

The site, named Nam Sing Ranch, was sold after the Chinese miner died at 75 in 1910. Now the land is divided between the Quesnel airport and a family ranch.

Wright, who made a 12-minute documentaryabout Chew's legacy two years ago with theNew Pathways to Gold Society,says he isn't sure how long Chew prospected in the Cariboo, but he ran a very successful business of freighting products from Quesnel to Barkerville, about 86 kilometres away, where residents suffered a shortage of fresh produce.

Wright says Chew hired many Indigenous people and those of Europeandescent as packers and cowboys.

"He was obviously a driven and determined individual," said Wright.

Besides the places named after Ah Bau and Chew, the B.C. government designated four other places in 2015 as locations of historical significance to Chinese Canadians, including Barlow Avenue in Quesnel.

Daybreak North8:02Early Chinese Canadian gold miners remembered for their contribution to the Cariboo communities

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Early Chinese Canadian gold miners remembered for their contribution to B.C.'s Cariboo communities - CBC.ca