Resource List

 

“Ask Anything” Universal Index

– September 29, 2016

MarkLogic uses an “Ask Anything” Universal Index that indexes data immediately when it is loaded, and you can immediately begin asking questions of your data.

 

An Introduction to NoSQL Technologies

, – September 26, 2016

Join Jim Driscoll as he talks all things NoSQL – get a better understanding of how NoSQL fits into the database universe and what kinds of problems it uniquely solves.

 

Hadoop Integration

– September 24, 2016

MarkLogic is the best database for Hadoop because it can seamlessly run alongside the Hadoop ecosystem, acting as the database to power real-time, transactional applications.

 

Flexible Data Model

– September 23, 2016

MarkLogic provides native storage for JSON, XML, RDF, geospatial, and large binaries (e.g., PDFs, images, videos). With this approach, it is easy to get all of your data in, and easy to make changes later on.

 

Flexible Deployment

– September 23, 2016

MarkLogic runs in any environment and you get to choose what environment to run it in. If you start on-premises and migrate to the cloud later on, that is okay.

 

Real-Time Alerting

– September 23, 2016

MarkLogic can handle hundreds of thousands of saved queries for alerting, and can send hundreds of millions of alerts per day.

 

MarkLogic Geospatial

– September 23, 2016

MarkLogic is the leading NoSQL database for geospatial applications, providing the ability to answer the “where” question in the context of any other operational data—all inside a platform designed with the security, scalability, and performance that organizations require.

 

MarkLogic ACID Transactions

– September 23, 2016

MarkLogic is an operational and transactional Enterprise NoSQL database that has had ACID transactions since its first version. MarkLogic’s ACID properties also apply to multi-document transactions, multi-statement transactions, and XA transactions (transactions across a cluster).

 

Bitemporal

– September 23, 2016

With MarkLogic, you can go back in time and explore data, manage historical data across systems, ensure data integrity, and do complex bitemporal analysis with ease.

 

Data Management Use Cases in Financial Regulation

– September 22, 2016

New and changing regulatory and competitive pressures require financial services institutions to increase transparency and make better use of the massive amounts of disparate and intricate data they use and produce each day. This whitepaper describes six key lessons learned from our work with global financial institutions who faced the challenge of reconciling information across their data silos.