Podcasts about dgraph

GraphQL was never conceived as a query language for databases. Yet, it's increasingly being used for this purpose. Here's why, and how. Manish Jain and Josh McKenzie are both engineer rock stars who wear many hats. They also have something else in common: they are both avid GraphQL users and builders, despite getting there from different start points. Article published on ZDNet

GraphQL has changed the common design patterns for the interface between backend and frontend. This is usually achieved by the presence of a GraphQL server, which interprets and federates a query from the frontend to the backend server infrastructure. Dgraph is a distributed graph database with native GraphQL support. Manish Jain is a founder of The post Dgraph: Native GraphQL Database with Manish Jain appeared first on Software Engineering Daily.

GraphQL has changed the common design patterns for the interface between backend and frontend. This is usually achieved by the presence of a GraphQL server, which interprets and federates a query from the frontend to the backend server infrastructure. Dgraph is a distributed graph database with native GraphQL support. Manish Jain is a founder of The post Dgraph: Native GraphQL Database with Manish Jain appeared first on Software Engineering Daily.

GraphQL has changed the common design patterns for the interface between backend and frontend. This is usually achieved by the presence of a GraphQL server, which interprets and federates a query from the frontend to the backend server infrastructure. Dgraph is a distributed graph database with native GraphQL support. Manish Jain is a founder of The post Dgraph: Native GraphQL Database with Manish Jain appeared first on Software Engineering Daily.

GraphQL has changed the common design patterns for the interface between backend and frontend. This is usually achieved by the presence of a GraphQL server, which interprets and federates a query from the frontend to the backend server infrastructure. Dgraph is a distributed graph database with native GraphQL support. Manish Jain is a founder of Dgraph, and joins the show to talk about its purpose and his vision for the future of the technology.

Eric Anderson (@ericmander) and Manish Jain (@manishrjain) discuss the impact of Dgraph, an open-source database with a graph backend that Manish describes as “a search engine acting as a database.” Manish took a gamble when he chose GraphQL as his project’s query language shortly after its release by Facebook in 2015. Now, GraphQL has grown immensely in popularity and the bet has paid off, as Dgraph leads the cutting edge of databases in this new space. Make sure to check out the Dgraph team’s conference, “GraphQL In Space,” which will be held virtually on September 10th at graphqlcon.space. In this episode we discuss: How Manish was ahead of the curve at Google The chance circumstances in the Australian job market that led to Dgraph Building trust between open-source developers and their community Why the Dgraph team decided to hold their upcoming conference “In Space” The future of databases and GraphQL Related Links: Dgraph GraphQL In Space GraphQL Badger MongoDB BigTable Cassandra Spanner Elasticsearch People mentioned: Scott Kelly (@StationCDRKelly)

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.08.13.249649v1?rss=1 Authors: Braun, B. A., Schein, C. H., Braun, W. Abstract: Motivation: There is a need for rapid and easy to use, alignment free methods to cluster large groups of protein sequence data. Commonly used phylogenetic trees based on alignments can be used to visualize only a limited number of protein sequences. DGraph, introduced here, is a dynamic programming application developed to generate 2D-maps based on similarity scores for sequences. The program automatically calculates and graphically displays property distance (PD) scores based on physico-chemical property (PCP) similarities from an unaligned list of FASTA files. Such PD-graphs show the interrelatedness of the sequences, whereby clusters can reveal deeper connectivities. Results: PD-Graphs generated for flavivirus (FV), enterovirus (EV), and coronavirus (CoV) sequences from complete polyproteins or individual proteins are consistent with biological data on vector types, hosts, cellular receptors and disease phenotypes. PD-graphs separate the tick- from the mosquito-borne FV, clusters viruses that infect bats, camels, seabirds and humans separately and the clusters correlate with disease phenotype. The PD method segregates the {beta}-CoV spike proteins of SARS, SARS-CoV-2, and MERS sequences from other human pathogenic CoV, with clustering consistent with cellular receptor usage. The graphs also suggest evolutionary relationships that may be difficult to determine with conventional bootstrapping methods that require postulating an ancestral sequence. Copy rights belong to original authors. Visit the link for more info

Manish Jain and Karl McGuire of Dgraph join Johnny and Jon to discuss caching in Go. What are caches, hit rates, admission policies, and why do they matter? How can you get started using a cache in your applications?

Manish Jain and Karl McGuire of Dgraph join Johnny and Jon to discuss caching in Go. What are caches, hit rates, admission policies, and why do they matter? How can you get started using a cache in your applications?

Manish Jain and Karl McGuire of Dgraph join Johnny and Jon to discuss caching in Go. What are caches, hit rates, admission policies, and why do they matter? How can you get started using a cache in your applications?

Wir haben uns diesmal zum Thema Datenbanken und Python zusammen gesetzt. Datenbanken sind ein weites Feld und daher ist diese Sendung auch ein bisschen länger geworden. Shownotes Datenbanken Postgres MySQL MariaDB MongoDB CouchDB Dgraph Neo4j Redis InfluxDB TimescaleDB Lucene Solr Elastichsearch Python ORM Django SQLAlchemy Pony peewee "Big Data" Ibis Arrow pyspark Papers A Relational Model of Data for Large Shared Data Banks C-Store: A Column-oriented DBMS Picks Sqlite Datasette Async binary driver for postgres Pickle Quellen Data serialization formats Taking a tour of postgres Everything is miscellaneous Method Chaining Implementing faceted search with Django and PostgreSQL Data Warehousing for Cavemen

This week we talk with Manish Jain about Dgraph, graph databases, and licensing and re-licensing woes. Manish is the creator and founder Dgraph and we talked through all the details. We covered what a graph database is, the uses of a graph database, and how and when to choose a graph database over a relational database. We also talked through the hard subject of licensing/re-licensing. In this case, Dgraph has had to change their license a few times to maintain their focus on adoption while respecting the core ideas around what open source really means to developers.

This week we talk with Manish Jain about Dgraph, graph databases, and licensing and re-licensing woes. Manish is the creator and founder Dgraph and we talked through all the details. We covered what a graph database is, the uses of a graph database, and how and when to choose a graph database over a relational database. We also talked through the hard subject of licensing/re-licensing. In this case, Dgraph has had to change their license a few times to maintain their focus on adoption while respecting the core ideas around what open source really means to developers.

The way that you store your data can have a huge impact on the ways that it can be practically used. For a substantial number of use cases, the optimal format for storing and querying that information is as a graph, however databases architected around that use case have historically been difficult to use at scale or for serving fast, distributed queries. In this episode Manish Jain explains how DGraph is overcoming those limitations, how the project got started, and how you can start using it today. He also discusses the various cases where a graph storage layer is beneficial, and when you would be better off using something else. In addition he talks about the challenges of building a distributed, consistent database and the tradeoffs that were made to make DGraph a reality.