MarkLogic
How to Bolster Data and AI Projects with MarkLogic Flux
November 04, 2024
Data exists everywhere in the enterprise and comes in various shapes, sizes and formats. Organizations need just-in-time, scalable and long-term solutions to support any operational, transactional, analytical or AI workload. Learn how MarkLogic Flux effectively automates high-volume, high-velocity heterogeneous data jobs to streamline data ingestion and data access to and from your MarkLogic-powered data platform.
Four Ways to Regroup After Implementing Hadoop
“Thru 2018, 70 percent of Hadoop deployments will not meet cost savings and revenue generation objectives due to skills and integration challenges.” – Nick Heudecker, Gartner Analyst A Gartner research report on Apache Hadoop found that 46 percent of companies surveyed plan Hadoop investments, marking a slow but steady adoption. However, there are still questions […]
How to use MarkLogic in Apache Spark applications
By now you may have heard that Apache Spark is the fastest growing project in open source ‘Big Data’ community. Spark does not include its own distributed data persistence technology but can work with any Hadoop-compatible data formats. You can use the MarkLogic Connector for Hadoop as an input source to Spark and take advantage of the Spark framework to develop your ‘Big Data’ applications on top of MarkLogic.
Finding the Right Balance with MarkLogic
Rebalancing in MarkLogic redistributes content in a database so that the forests that make up the database each have a similar number of documents. Spreading documents evenly across forests lets you take better advantage of concurrency among hosts.
How MarkLogic Supports ACID Transactions
A key feature of MarkLogic is ACID compliance. ACID stands for atomicity, consistency, isolation, and durability, and meeting these four requirements means that transactions in MarkLogic are reliable.
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