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With the addition of new data structures in Lucene 6.0, the Elasticsearch 5.0 release delivered massive indexing and search performance improvements for one-dimension numeric, date, and IP fields, and two-dimension (lat, lon) geo_point fields. Building on this work, the Elasticsearch 6.0 release further improved usability and simplicity of the geo_point API by setting the default indexing structure to the new block k-d tree (BKD) and removing all support for legacy prefix tree encoding.

As part of Elasticsearch 7.5.0, a new ingest processor — named enrich processor — was released. This new processor allows ingest node to enrich documents being ingested with additional data from reference data sets. This opens up a new world of possibilities for ingest nodes.

What does the revamped, modern technology stack of a 185-year-old Australian news corporation look like? In an industry that faces serious competition from anyone with a WordPress site and something to say, Nine Publishing, producer of Australia’s three largest news sites, sought to preserve a competitive edge by understanding how to enrich the experiences of their readers and journalists, while simultaneously identifying pain points and spotting problems before they happen.

This is a technical deep dive into the authentication process — a necessary first step before addressing the authorization decisions that are at the core of Elasticsearch security. The following will be a very detailed explanation of the inner workings of a key part of the authentication process: realms. If you'd prefer to start with a broader view of authentication (and authorization) in Elasticsearch, you may want to check out Demystifying authentication and authorization in Elasticsearch.

Elasticsearch is a powerful distributed search engine that has, over the years, grown into a more general-purpose NoSQL storage and analytics tool. The recent release of Elasticsearch 7 added many improvements to the way Elasticsearch works. It also formalized support for various applications including machine learning, security information and event management (SIEM), and maps, among others, through a revamped Kibana.

CHAOSSEARCH is building a new standard (a new category) in data analytics. Beyond the cost and complexity of Warehousing, Hadoop, or even Elasticsearch solutions. CHAOSSEARCH is a new kind of big data platform that delivers both search and analytics at a price and simplicity yet experienced. At CHAOS, we are primarily focused on transforming object storage (such as S3) into the first multi-model database, where the user provides read-only access to their S3 storage and CHAOS provides the rest.