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“Major milestone for Big Data” as Elasticsearch 1.0.0 GA goes live

Lucy Carey

Apache Lucene based open source search engine ships with new aggregation and analytics tools, federated analytics, and new backup and restore capabilities.

Ultra-hip’ and and ‘distributed REST’ aren’t phrases you’d naturally connect – but this improbable combination of attributes is part of what makes Elasticsearch so popular. Launched four years ago, the Java based open source search engine has had over six million downloads – and with a retooled new version 1.0.0 going GA this week, it’s just got that bit more ‘fetch’.

Among those millions of adopters, there are some pretty big names, including  Foursquare, Soundcloud and Github, drawn in by the “unique holy triangle” of capabilities offered by the engine, including data exploration capabilities, unstructured search, structured search, and aggregations or analytics.

According to creator Shay Banon, “By combining those three areas in a single product, users find themselves empowered with what they can do with their data.”

All of this sits on the foundation of Apache nestling Lucene 4.6.1 – or, if you like, Elasticsearch is “a piece of infrastructure built around Lucene’s Java libraries.” Whilst Elasticsearch provides a concise, user friendly ApI and scalability, all things that relate to the algorithms for matching text and stashing optimized indexes of searchable terms is implemented by Lucene. Also bundled with this is a set of operational tools provided by Elasticsearch.

The new 1.0.0 implementation seeks to build on Elasticsearch’s early success with a wealth of new features that certainly will make it a more attractive search proposition still for enterprise.

These additions include new aggregation and analytics tools for performing high-level queries, a zippy  “distributed percolation” add-on which enables an “alert-like” function, federated analytics, and new backup and restore capabilities, with incremental snapshots. All of this is the result of a nine months of  hard-core development work, with 8000 Commits logged by 183 dedicated coders.

Elasticsearch 1.0.0 cleans up with some inconsistent APIs that dogged the previous release, however, in certain instances, this is at the expense of backward compatibility – for this reason, it’s a good idea to read through the migration guide provided before updating.

Judging from the Twittersphere at least, there’s a lot of excitement around these developments, with the CTO of writing:

Speaking about the release, Banon commented that, “Business leaders want actionable insights, but they also want a solution that will have the scale, stability, and robust features to grow as their business grows. That is what we are delivering with 1.0.”
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