Elasticsearch is a rising star! Before it was launched, there were already frameworks such as Solr and Lucene, but they still couldn't stop the rise of Elasticsearch!
In the technical field, there is competition between languages, frameworks and frameworks, and communities and communities. Elasticsearch has never lacked competition since its birth. However, Elasticsearch is becoming more and more successful!
Every time you look at the development of a technology, it is like watching a top of the wave, which can make people excited!
Back in 2010, a young guy named Shay Banon started writing a search engine to help his wife manage an increasingly rich menu in his free time. His first iteration was called Compass. The second iteration is Elasticsearch. Before that, both Solr and Lucene had been born, and they both contained the golden key and belonged to the famous Apache project.
Solr was first released to open source in 2006, has long occupied the search engine field, and is the first choice for anyone who needs search functions.
Before Elasticsearch, Solr is actually very mature and has very rich functions, not just simple text indexing and searching; such as faceting, grouping, powerful filtering, insertable document processing, insertable search Chain components, language detection, etc.
Although, the powerful Solr has occupied a dominant position in the search field for many years. Then, around 2010, Elasticsearch became another option on the market.
Solr is so successful that it has some arrogance. For example, it does not provide near real-time search that was originally provided by Lucene. For another example, Solr's original version compatibility was poor, and it was far away from the community for various reasons, which led to its unsatisfactory development.
Moreover, Elasticsearch also uses Lucene, so from the beginning, Solr did not take Elasticsearch seriously.
Elasticsearch is not afraid of tigers and has no compatibility issues. It also launched the NRT near real-time search function from the beginning, which is widely liked by the community. At the same time, every new feature of Elasticsearch is as close to the community as possible. Solr is more troublesome to use, Elasticsearch simplifies the installation, including it does not require ZooKeeper (there is Zen Discovery or ZooKeeper inside) and so on.
Later, although they are all developing at a high speed, Elasticsearch chose a more realistic RESTful search engine. Moreover, Elastic company later released many important functions through acquisitions, such as: Logstash, Kibana, Marvel, Shield, Beats, Watcher, etc.
In the era of cloud computing, many established commercial companies have not seized the opportunity, such as Oracle. However, Elasticsearch is closely integrated with cloud computing, launching Elastic Cloud to facilitate management and orchestration.
Elastic went public on October 6, 2018, and it rose sharply on the first day. Those who are interested can read my article on October 6th last year.
The rise of Elasticsearch, in addition to the technology itself and commercial success, is more importantly that there are too many modern search requirements, almost all large companies are using it, including the 8.4TB email metadata leaked by Shanghai Jiaotong University some time ago Many universities are also using it.
