Adobe Target vs. Apache Solr vs. Elasticsearch

If you're using the Adobe stack and tools to power your website, Target is a great solution to implement. I've utilized Target within two organizations, one running on Adobe Experience Manager (AEM), and the other on Adobe Magento. I don't see how companies could harness the full capacity of Target without also having Adobe Analytics integrated. This is their 'secret sauce' and might not be a good solution for companies who are invested in Google Analytics 360. Integration was straightforward but did require support from the Adobe team to implement successfully. While Target is a great tool for digital teams to support, you'll need your tech team aligned and available to support implementation.

Incentivized

Solr spins up nicely and works effectively for small enterprise environments providing helpful mechanisms for fuzzy searches and facetted searching. For larger enterprises with complex business solutions you'll find the need to hire an expert Solr engineer to optimize the powerful platform to your needs. Internationalization is tricky with Solr and many hosting solutions may limit you to a latin character set.

Incentivized

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

• This application gives us an incredible integration with Adobe Analytics that allows its operation to be the best and determine the performance of our website.
• It offers us an analysis based on user behavior and a web page customization option to adapt and meet the needs of those users.

Incentivized

• Easy to get started with Apache Solr. Whether it is tackling a setup issue or trying to learn some of the more advanced features, there are plenty of resources to help you out and get you going.
• Performance. Apache Solr allows for a lot of custom tuning (if needed) and provides great out of the box performance for searching on large data sets.
• Maintenance. After setting up Solr in a production environment there are plenty of tools provided to help you maintain and update your application. Apache Solr comes with great fault tolerance built in and has proven to be very reliable.

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

• This is something a lot of testing tools struggle with, but I think the WYSIWYG ("What you see is what you get") editor - or Visual Experience Composer (VEC) in Adobe terminology - could definitely use some work. It's a struggle to execute many tests beyond simple copy, color, placement changes, and even the features that do exist are often clunky if not altogether broken.
• The interface itself can be a bit counterintuitive in certain parts. If you are familiar with other tools, it's likely middle of the road in this respect; think much easier to understand than Monetate for instance, but a far cry from the simplicity of an Optimizely.
• It can be a bit buggy from time to time. The worst example is the frequency at which the tool will fail to save due to an error, but not inform you of this until you try to save, at which point your only option is to log out, log back in, and make all of your updates once again. It can become an extreme pain point at times, and I personally have just gotten into the habit of saving every couple of minutes to avoid a massive loss of productivity.

Incentivized

• These examples are due to the way we use Apache Solr. I think we have had the same problems with other NoSQL databases (but perhaps not the same solution). High data volumes of data and a lot of users were the causes.
• We have lot of classifications and lot of data for each classification. This gave us several problems:
• First: We couldn't keep all our data in Solr. Then we have all data in our MySQL DB and searching data in Solr. So we need to be sure to update and match the 2 databases in the same time.
• Second: We needed several load balanced Solr databases.
• Third: We needed to update all the databases and keep old data status.
• If I don't speak about problems due to our lack of experience, the main Solr problem came from frequency of updates vs validation of several database. We encountered several locks due to this (our ops team didn't want to use real clustering, so all DB weren't updated). Problem messages were not always clear and we several days to understand the problems.

• 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

We have a team of people trained on how to use the application and it integrates well with the other Adobe products we use. Our future roadmap of testing will require some complex scenarios which we hope Target will be able to accomplish

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

The recent UI update is a complete mess. It is difficult to navigate and find features that previously existed. The reactiveness of the page depending on window size is also ridiculous and it is absurd that depending on how large your window is, entire columns of functions will disappear with no indication that they are missing. The usability of the tool has fallen off a cliff.

Incentivized

It takes some time to deploy and currectly maintein it. And also, to learn how to use and integrate in the enviroment as well. Once you get theses steps done, it usability is very simple, and almost of the time it don't require no further attention on it. Even for maintence, if you deploy it on a cluster mode, it is very reliable and easy to take one host down.

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

i don't think we use the full functionalities of the tool, but to use the full functions, it's almost impossible (Too hard)

The bottleneck is never the software program

On several occasions, we have had the need to ask for help from the Adobe Target support team, and I must say that they have provided us with an excellent experience, as they take care of solving the problems quickly and with high precision

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

The instructor that came to train us was awesome and this training was very useful. I would recommend it for anyone who is going to be using this software. I only mark it lower because it is an added expense to an already expensive product, and a lot of the training covered the "Target" portion of the software (which again, we didn't use)

The training was very easy to understand, however it would have been more useful to my development team than me. It was also primarily over-the-phone, which is never as easy to follow as in-person. We ended up scheduling and paying for an in-person training session to supplement the online/phone training because it wasn't helpful enough.

Implement using a global mBox on the page so you can change any and everything over the traditional method. Traditional method is good if you do not have technical web dev resources, do not know Javascript/jQuery, or you have money to blow on mBox calls. Global deployment reduces mBox calls and allows you to touch many parts of the page easily. A lot more customizable

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

Incentivized

We seriously considered another software but because we use so many other Adobe products this made the most sense for us. If you are not dependent on other Adobe software and are a smaller company, in my opinion, Target may not be the best fit.

Incentivized

We tried to use both Elasticsearch and Swiftype with Drupal 8 but there are currently no good modules that integrate Drupal with those solutions. So Solr was really the only option for a Drupal 8 web site. It's not as easy to learn or use as Swiftype, but in the end I think it will be a little less expensive and offer more customization and flexibility.

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

• We have been able to run specific A/B tests that have shown an increase in conversion, which in turn has led to very large banked sales numbers for the year.
• We have been able to prove that using and automated Merchandising process did not decrease conversion. This allowed us to greatly increase efficiency by opening up resource time.

• It has enabled my organization to find information faster by being a one-stop service to search across content that were indexed from varying sources.
• By using synonyms and usual lemmatizations / stemming, it enabled discovery of new content following every search.

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