Elasticsearch vs. HP Autonomy Intelligent Universal Search (discontinued)

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

It does a decent job at its core functions (that other free software does just as well or better).

• 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 adheres to traditional Microsoft standards such as: fact-dump documentation with no coherent story or 'best practices' information, inability to automate common tasks, intentional obfuscation of its basic operations.
• It provides OK search results. Not great, but OK.

• 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

• There are about a dozen different config files to maintain, and the most important one is dynamically modified by Autonomy itself while it runs. Which means that it is impossible to automate the configuration or keep the configs in versioned source control. Even `cp *.cfg ~/cfgbak/` won't help you roll back a change, because it is never safe to restore a previous config. You'll be using `diff new.cfg old.cfg` a lot.
• The Linux port is poorly thought out. The binaries are named *.exe. The StartService.sh scripts contain both `echo 'Are you sure you want to start the service? Hit ctrl-C to cancel''; read dummy` and, I kid you not, a `chmod a+x /path/to/my/binary.exe`.
• Many features are poorly documented, leading to lots of back and forth with the support department just to answer basic questions like "what does this error code in my logs signify?"
• It seems to reinvent the wheel, poorly, everywhere. E.g. the scheduled backup feature rolls through a user-defined finite list of directories in which to store backups. On day 0 it uses directory 0, on day 1 it uses directory 1, and after day N it rolls back and overwrites directory 0. Why would this be preferable to using a single directory and naming zip files based on the current timestamp?

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

Management wants to see ROI on the (hefty) cost of purchasing this software, and has mandated that we continue using it. We would prefer to switch immediately.

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

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

• 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

• I have learned to tack a zero onto the end of any estimate I make for how long an Autonomy change will take in both planning and implementation.