Progress to Acquire MarkLogic - Learn More

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Everything From Data Tips and NoSQL Best Practices to Industry Specific Insights

January 23, 2023
MarkLogic helps agency decision-makers connect to their IT data quickly, make better decisions, become more agile, and solve their most difficult cyber challenges.
January 17, 2023
MarkLogic 11 introduces support for GraphQL queries that run against views in your MarkLogic database. Customers interested in or already using GraphQL can now securely query MarkLogic via this increasingly popular query language.
January 3, 2023
MarkLogic has been at the forefront of solving complex data challenges for over 20 years. The industry recognizes us as a leader, offering significant capabilities to help solve the world’s most critical and complex data challenges. I’m proud to share that this pioneering spirit will continue as we become part of Progress. About the Progress […]
December 20, 2022
A data platform lets you collect, process, analyze, and share data across systems of record, systems of engagement, and systems of insight.
December 15, 2022
More ways to analyze your multi-model data and integrate with your data ecosystem. Easier to deploy, manage, and audit – including in the Cloud.
September 15, 2022
We're all drowning in data. Keeping up with our data - and our understanding of it - requires using tools in new ways to unify data, metadata, and meaning.
August 2, 2022
Successfully responding to changes in the business landscape requires data agility. Learn what visionary organizations have done, and how you can start your journey.
July 28, 2022
This not-too-technical article covers a number of questions about MarkLogic Server and its use of memory. Learn more about how MarkLogic uses memory, why you might need more memory, when you need more memory, and how you can add more memory.
July 21, 2022
A knowledge graph – a metadata structure sitting on a machine somewhere – has very interesting potential, but can’t do very much by itself. How do we put it to work?
July 5, 2022
Sharing data can be relatively easy. Sharing our specialized knowledge about data is harder - and current approaches don't scale.