Elasticsearch vs. OpenText LoadRunner Professional

Elasticsearch is a really scalable solution that can fit a lot of needs, but the bigger and/or those needs become, the more understanding & infrastructure you will need for your instance to be running correctly. Elasticsearch is not problem-free - you can get yourself in a lot of trouble if you are not following good practices and/or if are not managing the cluster correctly. Licensing is a big decision point here as Elasticsearch is a middleware component - be sure to read the licensing agreement of the version you want to try before you commit to it. Same goes for long-term support - be sure to keep yourself in the know for this aspect you may end up stuck with an unpatched version for years.

Incentivized

Micro Focus LoadRunner and its suite of tools, specifically VuGen works wonderfully for us for all web, http/https and web service calls. We've been able to build tests for near any scenario we need with relative ease. As long as we have crafted up requirements for our scenarios / scripts to managed scope, we've had high success working with scripting and data driving. Our main tests are web service calls - typically chained together to form a full scenario with transactions measuring the journey or a similar (measure along the way) journey through a browser. For web services we will use VuGen and browser we've shifted to Tru Client I have had little-to-no experience scripting against a thick client where a ui-driven test would be required. I know its possible but quite costly due to the need to run the actual desktop client to drive tests. We've been fortunate enough to leverage http calls to represent client traffic.

Incentivized

• As I mentioned before, Elasticsearch's flexible data model is unparalleled. You can nest fields as deeply as you want, have as many fields as you want, but whatever you want in those fields (as long as it stays the same type), and all of it will be searchable and you don't need to even declare a schema beforehand!
• Elastic, the company behind Elasticsearch, is super strong financially and they have a great team of devs and product managers working on Elasticsearch. When I first started using ES 3 years ago, I was 90% impressed and knew it would be a good fit. 3 years later, I am 200% impressed and blown away by how far it has come and gotten even better. If there are features that are missing or you don't think it's fast enough right now, I bet it'll be suitable next year because the team behind it is so dang fast!
• Elasticsearch is really, really stable. It takes a lot to bring down a cluster. It's self-balancing algorithms, leader-election system, self-healing properties are state of the art. We've never seen network failures or hard-drive corruption or CPU bugs bring down an ES cluster.

Incentivized

• It can simulate multiple users at the same time and help understand the performance.
• It can generate excellent reports and give insights into application performance.
• It is a fast tool and does not take time to perform its functions.

Incentivized

• Joining data requires duplicate de-normalized documents that make parent child relationships. It is hard and requires a lot of synchronizations
• Tracking errors in the data in the logs can be hard, and sometimes recurring errors blow up the error logs
• Schema changes require complete reindexing of an index

Incentivized

• HP LoadRunner with new patches and releases sometimes makes no longer support older version of various protocols like Citrix, which makes the task time-consuming when using older versions of LoadRunner for some of the cases. So it should support older version as well while upgrading.
• Configuring HP LoadRunner over the firewall involves lots of configuration and may be troublesome. So, there should be a script (power shell script for Windows or shell script for Linux users) to make it easy to use and with less pain.
• I would like to see the RunTime Viewer of Vugen in HPLoadRunner based on the browser I selected in the run-time configuration to make it feel more realistic as a real user.
• Licensing cost is very high when we need to perform a test on application for a specific group of users.

Incentivized

We're pretty heavily invested in ElasticSearch at this point, and there aren't any obvious negatives that would make us reconsider this decision.

Incentivized

To get started with Elasticsearch, you don't have to get very involved in configuring what really is an incredibly complex system under the hood. You simply install the package, run the service, and you're immediately able to begin using it. You don't need to learn any sort of query language to add data to Elasticsearch or perform some basic searching. If you're used to any sort of RESTful API, getting started with Elasticsearch is a breeze. If you've never interacted with a RESTful API directly, the journey may be a little more bumpy. Overall, though, it's incredibly simple to use for what it's doing under the covers.

Incentivized

We've only used it as an opensource tooling. We did not purchase any additional support to roll out the elasticsearch software. When rolling out the application on our platform we've used the documentation which was available online. During our test phases we did not experience any bugs or issues so we did not rely on support at all.

Incentivized

Customer service is not that great. It's difficult to get hold of someone if an issue is supposed to be addressed on an urgent basis. No online chat service readily available.

Incentivized

Do not mix data and master roles. Dedicate at least 3 nodes just for Master

Incentivized

As far as we are concerned, Elasticsearch is the gold standard and we have barely evaluated any alternatives. You could consider it an alternative to a relational or NoSQL database, so in cases where those suffice, you don't need Elasticsearch. But if you want powerful text-based search capabilities across large data sets, Elasticsearch is the way to go.

Incentivized

HP performance center stacks up very well for front end applications. Need more improvements for API performance testing.

Incentivized

• We have had great luck with implementing Elasticsearch for our search and analytics use cases.
• While the operational burden is not minimal, operating a cluster of servers, using a custom query language, writing Elasticsearch-specific bulk insert code, the performance and the relative operational ease of Elasticsearch are unparalleled.
• We've easily saved hundreds of thousands of dollars implementing Elasticsearch vs. RDBMS vs. other no-SQL solutions for our specific set of problems.

Incentivized

• The scripts created with traditional web/http protocol are not robust thus re-scripting is required after most every code drop. Troubleshooting and fixing the issue takes more time therefore in most cases we do re-scripting to keep it simple and save time.
• In ideal world you would rather spend more time doing testing than scripting in that case mostly you could use an Ajax TruClient protocol. This type of script will only fail when an object in the application is removed or changed completely. This way of scripting will save you more time and helps you maintain the scripts with less re-work effort on a release basis. On the long run you will have a better ROI when you use Ajax TruClient protocol for scripting.

Incentivized