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ChaosSearch Data Lake Platform is First to Unlock JSON Files for Analytics at ScaleChaosSearch today announced JSON Flex™, a powerful new capability that delivers a first-of-its-kind, scalable, cloud-native solution for analyzing JavaScript Object Notation (JSON) log files. The ChaosSearch Data Lake Platform can now help data engineers reduce the cost, complexity and time associated with accessing and analyzing complex nested JSON files. The company will demonstrate these enhancements at AWS re:Invent, taking place November 29 to December 3 in Las Vegas. The JSON file format has become a standard for logging, and it's common for data engineers to have heavily nested JSON within custom logs like CloudTrail and Sidecar. However, the JSON format requires significant preparation and transformation to present it for analysis - and the flattening of JSON can result in exploding data volume growth. These issues often prohibit companies from making JSON files available for on-demand analytics. Data engineers have limited options: they can either exclude and/or transform JSON via complicated data pipelines where such pipelines need to be revisited if requirements change; or at worst, fully expand all the JSON permutations upfront with the drawback of data explosion. These options create challenges for the business analysts who want access to all of the data and the ability to experiment with various searches as part of their analysis. To solve these challenges, ChaosSearch has created JSON Flex, which allows organizations to store all their JSON content and analyze it, as if structured, at different permutations and nested levels. ChaosSearch enables organizations to both keep and analyze all data efficiently and compactly without losing fidelity of insights. Customers can use the patented Chaos Refinery to expand and explore all JSON data virtually and instantly on the fly, regardless of size or query structure. JSON Flex eliminates the time sensitive process of data preparation, and individuals outside of IT can access critical insights that drive business decisions. With JSON Flex, users can:
"Until the introduction of JSON Flex, there hasn't been a scalable analytics solution for complex, nested JSON files," said Thomas Hazl, CTO, Founder and Chief Scientist, ChaosSearch. "Organizations have been forced to rely on static, limited views of their data that ultimately lead to less valuable insights. We're unlocking that data and democratizing it for the masses by delivering a platform that can automatically index and present all the data at once -- making it easier to search, understand and leverage for business insights." ChaosSearch also announced a new capability to perform logical "relational inner joins" of log sources within the ELK stack. Until now, correlating log sources required a pipeline to aggregate, de-normalize and ship logs from multiple sources into a single object store prior to ingestion. With the ChaosSearch inner join capability, customers can ingest raw data from multiple log sources into multiple object stores and then perform relational inner joins in the Chaos Refinery where they can perform dynamic, conditional transforms and join multiple data sources into a single view (e.g., Index patterns, relational tables). This further reduces the need for data prep and pipelines and lets users experiment with log sources dynamically so they can create insights faster.
About the ChaosSearch Data Lake Platform
About ChaosSearch
ChaosSearch was purpose-built for cost-effective, highly scalable analytics encompassing full text search, SQL and machine learning capabilities in one unified offering. The patented ChaosSearch technology instantly transforms your cloud object storage (Amazon S3, Google (News - Alert) Cloud Storage) into a hot, analytical data lake. The Boston-based company raised $40M Series B in December 2020 and is hiring to support its hyper growth. For more information, visit ChaosSearch.io or follow us on Twitter @ChaosSearch and LinkedIn.
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