Amazon Elasticsearch Service vs. IBM Watson Content Analytics

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

IBM Content Analytics is well suited for organizations with the resources to invest a significant amount of energy in an advanced analytics engine. The software improved the productivity of analysts and programmers. The software is not suitable for companies that just want Excel-type analyses or that lack the capabilities of doing advanced analytics.

Incentivized

• Fast Index based search.
• Scalable.
• Best for structured and unstructured data.

• Impressive and efficient indexing system.
• Rarely does the indexing have issues that need to rebuild/reindex.
• Searches are almost instantaneous and end users can move on to the next task.

Incentivized

• Really satisfied with this service from Amazon.

Incentivized

• It would be better if its available for cross platforms.
• Pricing could be adjusted better.
• More number of third party add-ons required.

Incentivized

Perhaps the biggest advantage of IBM Watson Content Analytics is the IBM feel. I think IBM puts lots of resources into developing products that even sociologists can use. It's so easy, that to professionals wanting customized analysis, it might be kind of offensive. The drawback is that Content Analytics is not as fast as its competitors.

Incentivized

• Elasticsearch has allowed us to spend more time on building features and less time on optimizing search queries

Incentivized

• Organized, easy to produce search results.
• Never lose a document again.

Incentivized