Share your experience using IBM StoredIQ InstaScan

The main use case for Elastic Search is mainly for log management.

I appreciate the indexing capabilities and the speed of indexing in their product, which demonstrates how quickly logs are collected and stored. The search capabilities are also valuable.

The architecture of Elastic Search could be improved as it is complicated for most general users to build up the environment and maintain the cluster.

Currently, I do not have suggestions for additional functions that could be added to the product.

I have been working with Elastic Search for about two years.

I usually use Elastic Search on-premises, which introduces complexity in deployment. Using the cloud version would reduce the complexity of setting up.

I would rate the stability for Elastic Search as eight out of ten.

I would rate the scalability as eight.

I would rate technical support from Elastic Search as three out of ten.

The main issue is a general sum of all factors. Being based in Hong Kong means I can only assess the service in my region and cannot speak for other regions based on my experience.

Negative

I am currently working with multiple solutions including Elastic Search, Splunk, and Graylog.

The initial setup for Elastic Search is complex.

The real-time analytics capabilities depend on whether you use the paid version or open-source version.

I work with SME users of Elastic Search, though the solution can technically support enterprise customers.

I have not extensively used AI technology with Elastic Search.

I can recommend Elastic Search to other users.

The pricing for Elastic Search rates as four out of ten. Overall, I would rate Elastic Search as seven out of ten.

On-premises

I have been using it for a year. The main use cases involved implementing search functionality.

When discussing the features of Elastic Search, the full text search capabilities are particularly beneficial for handling large volumes of data.

The full text search capabilities in Elastic Search have proven to be extremely valuable for our operations.

Regarding AI integration, we have not yet implemented any AI-driven projects or initiatives using Elastic Search.

There are some features and functionality that could be enhanced in Elastic Search to improve its overall capabilities.

I have been using Elastic Search for a year.

In terms of performance and stability, Elastic Search has proven to be a reliable solution.

The environment includes multiple users utilizing Elastic Search across different locations.

Before implementing Elastic Search, I had experience working with other search engines from different vendors.

The implementation strategy involved specific steps during the setup process to ensure proper configuration.

The main benefits observed from using Elastic Search include improvements in operational efficiency, along with cost, time, and resource savings.

I previously used Graylog.

I am currently working with Elastic Search as the primary solution.

My role is Senior DevOps engineer at UVIK Digital.

On a scale of 1 to 10, with 10 being the highest, I would rate Elastic Search as an 8 overall as a product and solution.