Elasticsearch is an enterprise search tool from Elastic in Mountain View, California.
$16
per month
LoadRunner Professional
Score 8.6 out of 10
N/A
A solution simplifies performance load testing for colocated teams. With project-based capabilities, so teams can quickly identify abnormal application behavior.
N/A
Redis Software
Score 9.1 out of 10
N/A
Redis is an open source in-memory data structure server and NoSQL database.
N/A
Pricing
Elasticsearch
OpenText LoadRunner Professional
Redis Software
Editions & Modules
Standard
$16.00
per month
Gold
$19.00
per month
Platinum
$22.00
per month
Enterprise
Contact Sales
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Elasticsearch
LoadRunner Professional
Redis Software
Free Trial
No
No
Yes
Free/Freemium Version
No
No
Yes
Premium Consulting/Integration Services
No
No
Yes
Entry-level Setup Fee
No setup fee
No setup fee
Optional
Additional Details
—
—
—
More Pricing Information
Community Pulse
Elasticsearch
OpenText LoadRunner Professional
Redis Software
Considered Multiple Products
Elasticsearch
Verified User
Engineer
Chose Elasticsearch
Elasticsearch has a steep learning curve, but it is the best in terms of customization and use cases it can cover most of the business needs. The other tools might be easier to integrate with and start seeing results, but you will end up having issues when you need customized …
All database systems have things they are good at, and things they aren't as good at. Riak/SOLR is great as a K/V store, but SOLR cannot handle requests as fast as ElasticSearch. In fact, SOLR is the reason we had to migrate to ElasticSearch. Redis is great at SET operations …
ES does not compete with the above packages but compliments them. By automating and mining logs, you are able to get a sense of the business process, marketing data or whatever else you need to capture and mine. The potential energy stored within Elasticsearch makes it a great …
Verified User
Manager
Chose Elasticsearch
We found Elasticsearch to be the fastest in querying text based data, allowing us to significantly speed up our APIs.
We first started out experimenting with PostgreSQL's fulltext searching capabilities for our project. As our dataset grew, PostgreSQL began to slow down too much for our purposes. The simple fact that Elasticsearch has built-in clustering and replication was enough for us to …
Redis is great at set operations and is very fast. Riak is a fast long-term data store, but it is expensive to run. MongoDB is good for small, quick projects. Elasticsearch is great at indexing and searching. Choose the right tool for the job, and don't be afraid to …
We chose Redis over Memcached and Couchbase for its performance, cost, support, and ease of use. Couchbase probably would have worked as well, but it seemed a bit overkill for our use cases.
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.
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.
Redis has been a great investment for our organization as we needed a solution for high speed data caching. The ramp up and integration was quite easy. Redis handles automatic failover internally, so no crashes provides high availability. On the fly scaling scale to more/less cores and memory as and when needed.
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.
Easy for developers to understand. Unlike Riak, which I've used in the past, it's fast without having to worry about eventual consistency.
Reliable. With a proper multi-node configuration, it can handle failover instantly.
Configurable. We primarily still use Memcache for caching but one of the teams uses Redis for both long-term storage and temporary expiry keys without taking on another external dependency.
Fast. We process tens of thousands of RPS and it doesn't skip a beat.
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.
We had some difficulty scaling Redis without it becoming prohibitively expensive.
Redis has very simple search capabilities, which means its not suitable for all use cases.
Redis doesn't have good native support for storing data in object form and many libraries built over it return data as a string, meaning you need build your own serialization layer over it.
We will definitely continue using Redis because: 1. It is free and open source. 2. We already use it in so many applications, it will be hard for us to let go. 3. There isn't another competitive product that we know of that gives a better performance. 4. We never had any major issues with Redis, so no point turning our backs.
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.
It is quite simple to set up for the purpose of managing user sessions in the backend. It can be easily integrated with other products or technologies, such as Spring in Java. If you need to actually display the data stored in Redis in your application this is a bit difficult to understand initially but is possible.
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.
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.
The support team has always been excellent in handling our mostly questions, rarely problems. They are responsive, find the solution and get us moving forward again. I have never had to escalate a case with them. They have always solved our problems in a very timely manner. I highly commend the support team.
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.
We are big users of MySQL and PostgreSQL. We were looking at replacing our aging web page caching technology and found that we could do it in SQL, but there was a NoSQL movement happening at the time. We dabbled a bit in the NoSQL scene just to get an idea of what it was about and whether it was for us. We tried a bunch, but I can only seem to remember Mongo and Couch. Mongo had big issues early on that drove us to Redis and we couldn't quite figure out how to deploy couch.
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.
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.
Redis has helped us increase our throughput and server data to a growing amount of traffic while keeping our app fast. We couldn't have grown without the ability to easily cache data that Redis provides.
Redis has helped us decrease the load on our database. By being able to scale up and cache important data, we reduce the load on our database reducing costs and infra issues.
Running a Redis node on something like AWS can be costly, but it is often a requirement for scaling a company. If you need data quickly and your business is already a positive ROI, Redis is worth the investment.
