Amazon Elasticsearch Service vs. HP Autonomy Intelligent Universal Search (discontinued)

Elasticsearch is a good alternative to relational databases for setting up complex searching of data. It's inbuilt features for slicing the data [in] different ways and its ability to add weights to search results makes it easy to set up complex searching scenarios. Given that data must be pushed to this service, it may be best suited for data that is not changing very rapidly.

Incentivized

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

• Search
• Query language
• light-weight

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.

• It is not so simple to learn.
• Documentation is often very confusing.

• 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?

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.

It is an extremely powerful tool if the time is put in to learn it. There are basic skeletons of out of the box behavior, it involves having really dedicated people to learn how to use it to take full advantage of its capabilities. A 10 for the tool itself, minus 3 for the difficulty in learning and maintenance

Incentivized

Splunk is the most flexible of the 3 where you can manipulate the data to whatever fits your specific use case. Grafana has the most powerful capabilities but the steepest learning curve. Grafana also does offer the most flexibility as you can visualize almost any data source. Elastic is a solid middle ground between the 2

Incentivized

• The cost is a bit expensive if compared with other clouds but [the] performance is very good.

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.