February 15, 2013 2 Comments
With Solr 4.1 recently released, let’s see which version(s) of Solr people are using. Please tweet it to help us get more votes and better stats.
Search, Big Data, Analytics, Natural Language Processing
January 22, 2013 4 Comments
One of the questions after my talk during the recent ApacheCon EU was what I thought about the communities of the two search engines I was comparing. Not surprisingly, this is also a question we often address in our consulting engagements. As a part of our Apache Solr vs ElasticSearch post series we decided to step away from the technical aspects of SolrCloud vs. ElasticSearch and look at the communities gathered around thesee two projects. If you haven’t read the previous posts about Apache Solr vs. ElasticSearch here are pointers to all of them:
January 8, 2013 3 Comments
In previous posts, all listed below, we’ve discussed general architecture, full text search capabilities and facet aggregations possibilities. However, till now we have not discussed any of the administration and management options and things you can do on a live cluster without any restart. So let’s get into it and see what Apache Solr and ElasticSearch have to offer.
December 6, 2012 1 Comment
We are happy to announce the General Availability of SPM, our performance monitoring solution for Apache Solr, ElasticSearch, HBase, SenseiDB, and Java applications, and of course all system metrics. You can also vote for what else you want SPM to monitor. Over the last N months that we’ve been running SPM we’ve received a lot of good feedback (thanks!), a lot of words of encouragement (thanks!), and even a few nice quotes (another thanks!). Here is one from Jerry Yang, a Software Engineer at Walmart Labs: “I have been using SPM for couple of days and it has been amazing. I learned a lot about my Solr services and was able to optimize based on the results on SPM. Great work.”
Since holiday season is coming up, we thought we’d offer some discounts every week between now until the end of the year. Each of the following discounts can be used only during “its week” specified below. There is a limit to the number of people who can use each discount, so if you want it, don’t waste too much time. Each discount will reduce the price of SPM SaaS for 365 days after you’ve used it, which effectively means you will get discount until the end of 2013. Note that when you register for SPM you do not need to enter your credit card information. You also don’t need to provide it when you create the SPM application for the system you want to monitor. And it is when you create your SPM application that you can enter the discount code.
Note that each discount code expires on Sunday at 00:00 UTC.
The above discounts are good for our SPM SaaS. However, if you’d rather run SPM on your own servers, we do offer SPM on Premises – please get in touch if you are interested in the on premises version. You can also vote for SPM SaaS vs. On Premise and that way tell us which version you prefer or want.
There are a few different subscription plans available in SPM SaaS:
If you have not used SPM before, here is what you can expect to see – click on the image to see a large, non-fuzzy version:
November 8, 2012 2 Comments
If you like working with Solr and/or ElasticSearch, or HBase, Hadoop, Kafka, Flume, etc., use and/or develop highly scalable distributed applications and frameworks, if you like to work on Analytics and Big Data applications and services, we’re looking for good, smart, and fun people!
October 30, 2012 4 Comments
Solr 4 (aka SolrCloud) has just been released, so it’s the perfect time to continue our ElasticSearch vs. Solr series. In the last three parts of the ElasticSearch vs. Solr series we gave a general overview of the two search engines, about data handling, and about their full text search capabilities. In this part we look at how these two engines handle faceting.
October 1, 2012 12 Comments
In the last two parts of the series we looked at the general architecture and how data can be handled in both Apache Solr 4 (aka SolrCloud) and ElasticSearch and what the language handling capabilities of both enterprise search engines are like. In today’s post we will discuss one of the key parts of any search engine – the ability to match queries to documents and retrieve them.
September 24, 2012 1 Comment
Apache Solr 4.0 release is imminent and we have a heavily anticipated Solr vs. ElasticSearch blog post series going on. What better time to share that our Rafał Kuć will be giving a talk titled Battle of the giants: Apache Solr 4.0 vs ElasticSearch at the upcoming ApacheCon/Lucene EuroCon in Germany this November.
In this talk audience will be able to hear about how the long awaited Apache Solr 4.0 (aka SolrCloud) compares to the second search engine built on top of Apache Lucene – ElasticSearch. From understanding the architectural differences and behavior in situations like split – brain, to cluster recovery. From distributed indexing and document distribution control, to handling multiple shards and replicas in a single cluster. During the talk, we will also compare the most used and anticipated features such as faceting handling, documents grouping and so on. At the end we will talk about performance differences, cluster monitoring and troubleshooting.
September 4, 2012 25 Comments
In the previous part of Solr vs. ElasticSearch series we talked about general architecture of these two great search engines based on Apache Lucene. Today, we will look at their ability to handle your data and perform indexing and language analysis.
August 23, 2012 13 Comments
A good Solr vs. ElasticSearch coverage is long overdue. We make good use of our own Search Analytics and pay attention to what people search for. Not surprisingly, lots of people are wondering when to choose Solr and when ElasticSearch, and this SolrCloud vs. ElasticSearch question is something we regularly address in our search consulting engagements.
As the Apache Lucene 4.0 release approaches and with it Solr 4.0 release as well, we thought it would be beneficial to take a deeper look and compare the two leading open source search engines built on top of Lucene – Apache Solr and ElasticSearch. Because the topic is very wide and can go deep, we are publishing our research as a series of blog posts starting with this post, which provides the general overview of the functionality provided by both search engines.