MarkLogic unveils the MarkLogic Data Hub Service

The new, fully automated cloud service provides the fastest and most cost-effective way to integrate data from silos and deliver on the unmet promise of Data Lakes.

  • 6 years ago Posted in

MarkLogic has launched the MarkLogic Data Hub Service, which provides the fastest and most cost-effective way for enterprises to integrate, store, harmonize, analyze and secure mission-critical data in the cloud. The MarkLogic Data Hub Service amplifies the power of MarkLogic’s industry-leading Data Hub technology by lowering the cost and operational burden of integrating large swaths of business and user data. This curated data fuels powerful analytical and transactional applications, IoT analysis, knowledge graphs, artificial intelligence and machine learning.


Organizations today are increasingly overwhelmed by data. As a result, they are gravitating towards solutions that are simple to use and provide more agility with less operational overhead. The MarkLogic Data Hub Service provides DevOps teams with all the agility they need to rapidly integrate data, but none of the operational overhead, meaning they can focus on “Dev,” not “Ops.” This is where the business value lies. Moreover, because the service is built on MarkLogic’s modern multi-model database, organizations don’t need to manually stitch together and manage multiple cloud services to address data integration needs.

Data Lakes Done Right

Data Lakes promised to help with the data deluge faced by all organizations but that promise has largely gone unmet. Top analyst firms have discussed the many causes, including a lack of governance, semantic inconsistency, and inflexibility. The MarkLogic Data Hub Service is built from the ground-up to address those challenges.

“The MarkLogic Data Hub Service is actually Data Lakes done right,” said Joe Pasqua, EVP and Head of Products at MarkLogic. “Data Lakes were pointed in the right general direction, but ignored basic realities of life in the enterprise. The MarkLogic Data Hub Service delivers on the promise of Data Lakes by making it simple to manage, curate, secure, operate and operationalize data to drive real business outcomes.”

“Data Hubs serve an important role in many modern-day enterprises today as they offer a means to effectively organize and manage an organization’s data,” said James Curtis, Senior Analyst at 451 Research. “Leveraging the company’s Data Hub solution, the new MarkLogic Data Hub Service offers enterprise functionality with built-in security while providing all of the conveniences of a cloud service.”

Variable Workloads, Predictable Cost

While workloads may vary from minute to minute, budgets do not. Enterprises need a predictable cost model that can adjust to varying demand. MarkLogic’s unique architecture allows resources to be added and removed from the underlying database in seconds, something that hasn’t been possible until now. The MarkLogic Data Hub Service uses the same technology that was first delivered in the MarkLogic Query Service to allow bursting to meet peak loads while providing a completely predictable cost aligned with baseline usage unlike an expensive, over-provisioned solution, or a costly and unpredictable on-demand approach.

“The ability to handle variable workloads with predictable cost, coupled with advanced security, is changing the game. Together they make a much broader set of workloads safe and cost-effective to move to the cloud, which accelerates digital transformation,” noted Pasqua.

Leapfrogging Database as a Service
The MarkLogic Data Hub provides important business value beyond what is seen in any database. It handles different data types (e.g. documents, graphs, relational, and geospatial) from different data sources (e.g. RDBMS, message buses, streaming data, etc.) to be integrated curated, mastered, governed, searched, queried, and harmonized within a single architecture. Trying to achieve similar capabilities with traditional approaches requires stitching together ten or more different components on top of a database, which results in higher costs, complexity, brittleness, and overhead.

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