The compatibility of this information with other programs, partners, and clients might involve restructuring or converting the data to another format. This makes databases inherently less “agile” than ...

It is expected that data lakes will reach an annual market volume of $20.1 billion by 2025, according to Research and Markets - despite the term being just over a decade old. The concept of the data ...

Data lake ETL platforms are available in a full range of options – from open-source to managed solutions to custom-built. Whichever tool you select, it’s important to differentiate data lake ETL ...

To gain insights, data must be transformed and moved out of the lake into an analytical database such as Splunk, MySQL, or Oracle, depending on the use case. This process is complex, slow, and costly.

A data lake is still a fairly new concept that refers to the storage of a large amount of unstructured and semi structured data. It addresses the need to store data in a more agile method compared to ...

Data Lake-as-a-Service provides big data processing in the cloud for business outcomes in a cost effective way. InfoQ spoke with Lovan Chetty & Hannah Smalltree from Cazena about these solutions work.

The data lake is a fundamental concept of data management. But what type of storage do you need to build a data lake on and what are the pros and cons of on-prem vs the cloud?

ChaosSearch, a leading log analytics platform, today announced the release of Chaos LakeDB – the first data lake database designed to power generative artificial intelligence (AI), SQL, and Live ...

The Finance Ministry's large database, also known as a data lake, is expected to help it design fiscal policies tailored to ...