Major milestone for Big Data as Elasticsearch 1.0.0 GA goes live
Apache Lucene based open source search engine ships with new aggregation and analytics tools, federated analytics, and new backup and restore capabilities.
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
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
This is a major milestone for Big Data. ElasticSearch v1.0 is
— Dominiek ter Heide (@dominiek) February
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.”