Announcements from Neo4j’s GraphConnect conference, Microsoft’s updates on Windows Dev Center, MapR’s launch of MapR Data Science Refinery, and more in today’s top data science news.
Graph database Neo4j in News
Graph database leader Neo4j has launched a new platform for developers to build graph-based applications using a common set of services. Breaking the announcement at its GraphConnect conference in New York, Neo4j said the new platform will help the graph databases connect to various enterprise systems allowing developers to build applications more quickly. Until now, customers were forced to create their own architecture to manually connect to these systems.
At its ongoing GraphConnect conference, Neo4j announced a new initiative to support the design and execution of graph queries in the Apache Spark environment. Neo4j released an early version of Cypher for Apache™ Spark® (CAPS) language toolkit to the openCypher project. This contribution will allow big data analysts to incorporate graph querying in their workflows, making it easier to bring graph algorithms to bear, dramatically broadening how they reveal connections in their data. Developers of Spark applications now join the users of Neo4j, SAP HANA, Redis Graph and AgensGraph, among others, in gaining access to Cypher, the leading declarative property graph query language. This also expands the tooling available to any developer, under Apache 2.0 licenses from the openCypher project.
Neo4j has announced its latest release – Neo4j 3.3. With Neo4j 3.3 write performance has improved with on average 50% compared to Neo4j 3.2, making it possible to ingest more data in less time. Bulk writes at initial graph creation reduces the memory footprint by up to 40%. The new Cypher Slotted Runtime results in faster queries while using one third of the memory compared to the Neo4j 3.2 Cypher Runtime. On security front, Neo4j 3.3 introduces new support for intra-cluster encryption, including multi-DC cluster communication encryption. The new version also brings new kernel improvements as it now allows key configuration parameters to be changed on the fly, without needing to recycle a database instance.
Microsoft in News
In Windows Dev Center, under the Review Reports, Microsoft is introducing a new feature called Review insights. Review insights uses machine learning to classify new app reviews, even non-English reviews, into one of 12 pre-defined categories. This will help developers to quickly understand customer sentiment by filtering their app’s reviews by category. Developers can also apply additional filters, such as OS version or rating, to further isolate issues and find actionable feedback.
MapR in News
MapR has unveiled MapR Data Science Refinery, a new solution that provides data scientists an easy way to access and analyze all data in-place, to collaborate, build and deploy machine learning models on the MapR Converged Data Platform. Using a developer friendly notebook and a wide range of open source data science tools that integrate directly with the MapR Platform, the MapR Data Science Refinery is easy to deploy using a secure, persistent, and extensible container that can be distributed to many data science teams across multi-tenant environments.
Other data science News
SQL database engine SQLite has released its version 3.21.0 where it added several new features and enhanced the running functionalities. The new version also contains a number of bug fixes.
Apache PredictionIO, an open source platform donated last year by Salesforce, has been promoted by the Apache Software Foundation (ASF) from the Apache Incubator to Top-Level Project (TLP), signifying that the project’s community and products have been well-governed under the ASF’s meritocratic process and principles. Apache PredictionIO focuses on enabling developers to quickly develop and deploy production-ready Machine Learning pipelines. The project features an engine template gallery, where developers can pick a template, and quickly ramp up a complete setup for their Machine Learning use cases. Apache PredictionIO is in use at ActionML, BizReach, LiftIQ, Pluralsight, and Salesforce, among others.
Baidu has launched the third version of Deep Voice which can dramatically shorten the learning time and support a higher number of language accents. Deep Voice 3 can learn as many as 2500 voices by processing the data in just 30 minutes. The Deep Voice projects use deep learning techniques to convert text to speech. Google has a similar project called WaveNet through its DeepMind unit. Baidu said the future versions may use even bigger data set and master up to 10,000 voices.
Amazon Aurora with PostgreSQL Compatibility is now generally available, Amazon announced on its official blog post. It is compatible with PostgreSQL 9.6.3 and scales automatically to support up to 64 TB of storage, with 6-way replication behind the scenes to improve performance and availability. Amazon Aurora with PostgreSQL Compatibility is fully managed and can perform up to 3x the throughput users otherwise get running PostgreSQL on their own.