MongoDB Announces Pricing of Upsized $1.0 Billion Convertible Senior Notes Offering

MongoDB, Inc., the leading modern, general purpose database platform, announced the pricing of $1.0 billion aggregate principal amount of 0.25% convertible senior notes due 2026 (the “notes”) in a private placement to persons reasonably believed to be qualified institutional buyers pursuant to Rule 144A under the Securities Act of 1933, as amended (the “Securities Act”).

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Tamarack Resort Chooses Ascent360 CDP To Accelerate Marketing Outreach

The Company’s Platform and Industry Expertise Create Efficiencies for the Resort
Ascent360, a leading customer database platform (CDP) provider for mid-market businesses, announced that Tamarack Resort has chosen the platform to help them achieve their marketing goals: building awareness and driving visitors to their family-friendly, four-seasons destination.

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Introducing New Book: Principles of Database Management – The Practical Guide to Storing, Managing and Analyzing Big and Small Data

Deep-Data-Mining is pleased to introduce the new book, Principles of Database Management – The Practical Guide to Storing, Managing and Analyzing Big and Small Data, by Lemahieu W., vanden Broucke S.,  and Baesens B. (ISBN: 9781107186125). The following is the book interview.See http://admin.cambridge.

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Understanding How Neo4j Cypher Queries are Evaluated

There are many ways to store and manage data within a Neo4j graph database. When Neo4j 2.0 launched late last year we had an entirely new browser experience for interacting with graphs. The graph visualization from the return results of Cypher queries were at the core of the user experience enhancements to the platform.

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The graph analytics landscape 2019

Read part 1 – The graph database landscape
The graph analytics landscape 2019
Graph analytics frameworks consist of a set of tools and methods developed to extract knowledge from data modeled as a graph. They are crucial for many applications because processing large datasets of complex connected data is computationally challenging.

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Creating an LMDB database in Python

LMDB is the database of choice when using Caffe with large datasets. This is a tutorial of how to create an LMDB database from Python. First, let’s look at the pros and cons of using LMDB over HDF5.
Reasons to use HDF5:
Simple format to read/write.
Reasons to use LMDB:
LMDB uses memory-mapped files, giving much better I/O performance.
Works well with really large datasets.

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