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Amazon re:Invent: Data partner news summary


Amazon Web Services' (AWS') re:Invent conference in Las Vegas, though it focuses broadly on the AWS cloud, has become a coming out party for the Seattle-based provider's data, analytics and AI-related services. But beyond that, re:invent is a data industry event, which many AWS partners in the data ecosystem use as their own vehicle for launches and announcements. While I am not attending the event this year, I did receive bulletins from a range of data- and analytics-focused companies each with their own announcements around offerings on the AWS cloud. Most of these announcements were made yesterday, making for a good "roll-up" opportunity today, and I'll summarize those announcements here. Lakefront product announcements First up, data management specialist Okera announced its new Introduces Intelligent Schema Management for Amazon S3 Data Lakes.

Knowledge graphs beyond the hype: Getting knowledge in and out of graphs and databases


We can officially say this now, since Gartner included knowledge graphs in the 2018 hype cycle for emerging technologies. Though we did not have to wait for Gartner -- declaring this as the "Year of the Graph" was our opener for 2018. Like anyone active in the field, we see the opportunity, as well as the threat in this: With hype comes confusion. They have been for the last 20 years at least. Knowledge graphs, in their original definition and incarnation, have been about knowledge representation and reasoning.

MemSQL 7.0: An all-in-one database for operational analytics and AI/ML-powered apps - Help Net Security


MemSQL, the No-Limits DatabaseTM for operational analytics and cloud-native applications, announced the general availability of MemSQL 7.0, the most powerful version yet of the company's all-in-one database for operational analytics and AI/ML-powered applications. Available as a managed service in the cloud via MemSQL Helios or self-deployed in cloud, containers or on-premise, MemSQL 7.0 delivers several new advances in database architecture, including "SingleStore," a breakthrough new way of managing data; enhanced system of record and resilience features that make MemSQL an even more trusted platform for Tier 1, mission-critical workloads; and time-series data management enhancements. The addition of SingleStore functionality differentiates MemSQL from other operational data platforms because of its innovative and unique data architecture that seeks to eliminate data duplication, reduce complexity and cut total cost of ownership. By bringing rowstore and columnstore tables together in a single database, SingleStore eliminates ETL and allows SQL queries to combine data from both types of tables. SingleStore offers the fastest possible performance, at the lowest possible cost, for transactional, analytical and hybrid workloads.

Graph Databases Burst into the Mainstream


Whether for Customer Analytics, Fraud Detection, Risk Assessment or another real-world challenge, the ability to quickly and efficiently explore, discover and predict complex relationships is a huge competitive differentiator for businesses today. Getting it done involves more than merely connected data – it's about real-time and up-to-date correlation, detection and discovery. Organizations need to be able to transform structured, semi-structured and unstructured data and massive enterprise data silos into an intelligent, interconnected data network that can reveal critical patterns and insights to support business goals. This elemental pain point – the need for real-time analytics for enterprises with enormous volumes of data – is fueling graph databases' emergence as a mainstream technology being embraced by companies across a broad range of industries and sectors. Since seeing early adoption by companies including Twitter, Facebook and Google, the graph database market has been heating up.

Scalable Graph Database Technology: Combining Big Data and Real-Time Analytics - DATAVERSITY


In February of 2018, TigerGraph released the 2.0 version of its Graph Database platform, described as "the next evolutionary step for Graph Databases." TigerGraph was founded by its CEO, Dr. Yu Xu, in 2012. He is an expert in parallel database systems and Big Data. In 2011, while working Twitter, he said he discovered Graph Databases were seriously inadequate. As a result, he brought together 30 engineers and developed TigerGraph and their native parallel Graph Database system.