

Informatica Intelligent Data Management Cloud and Elastic Search are leaders in data management solutions. While IDMC focuses on comprehensive data management, Elastic Search emphasizes powerful search and analytics capabilities. Each product has its strengths, with IDMC excelling in data integration and Elastic Search in search functionality.
Features: IDMC integrates master data management, data quality, and data integration modules, offering robust data cleansing and address validation. Its flexible architecture supports large databases seamlessly. Elastic Search provides advanced search capabilities with real-time analytics through Kibana, high scalability, and the ability to handle extensive log data efficiently.
Room for Improvement: IDMC users would like a more user-friendly interface, improved error reporting, and enhanced connectivity. Elastic Search users seek enhancements in machine learning and simpler dashboard customizations in Kibana, as well as easier configuration management.
Ease of Deployment and Customer Service: IDMC provides deployment options across on-premises, cloud, and hybrid environments, receiving positive customer service feedback, with some time zone challenges. Elastic Search is cloud-based, praised for easy deployment and robust support, though users need a deep understanding of the platform for smooth integration.
Pricing and ROI: IDMC's pricing aligns with its extensive capabilities, providing significant ROI for master data tasks. Elastic Search offers a cost-effective solution, available as a free open-source or paid managed service, favored by businesses focused on budget efficiency, but requiring skilled personnel for optimal use.
We have not purchased any licensed products, and our use of Elastic Search is purely open-source, contributing positively to our ROI.
It is stable, and we do not encounter critical issues like server downtime, which could result in data loss.
The main benefits observed from using Elastic Search include improvements in operational efficiency, along with cost, time, and resource savings.
Leadership prefers to utilize third-party tools, such as Snowflake, which has both storage and ELT features.
The stability and performance remain issues.
Compared to Collibra Catalog, where the value is noticeable within six months.
The customer support for Elastic Search is one of the best I have ever tried.
They have always been really responsible and responsive to my requests.
It has been sufficient to visit conferences such as SCALE in Southern California Linux Expo, where Elastic Search has a booth to talk to their staff.
Due to the tool's maturity limitations, solutions are not always simple and often require workarounds.
Even after going out of service support, they still reached back to me whenever I raised tickets.
We expect more responsive assistance because they have the expertise since Informatica is their tool, but I don't see enough expertise on the Informatica support side.
I would rate its scalability a ten.
Since we're on the cloud, whenever we need to upgrade or add resources, they handle everything.
We haven't encountered any problems so far, and there is the potential for auto-scaling.
I have used the product over multiple systems and was able to write reports for large data sets without any performance issues.
As a SaaS platform, IDMC is quite scalable and provides complete flexibility.
There are many options available, and the licensing model is quite good, supporting our needs effectively.
The data transfer sometimes exceeded the bandwidth limits without proper notification, which caused issues.
The stability of Elasticsearch was very high.
When you put one keyword, everything related to that keyword in your ecosystem will showcase all the results.
Stability is crucial because IDMC holds business-critical data, and it needs to be available all the time for business users.
There are substantial stability issues with Informatica Cloud Data Quality on the cloud.
I find the stability to be good, with occasional restarts required every two to three months due to glitches.
From a technical point of view, there are no significant issues recalled as Elastic Search has been absolutely awesome for this use case and covers 100% of the needs.
If I need to parse one million records saved into Elastic Search, it becomes a nightmare because I need to do the pagination, and it is very problematic in that regard.
Observability features like search latency, indexing rate, and maybe rejected requests should be added to make the platform more reliable and accessible for everyone.
The tool needs to mature in terms of category-specific attributes or dynamic attributes.
The current solution requires code-writing and tweaking, while other solutions offer material-level matches.
If the development interface could be optimized to have fewer modules, it would be greatly beneficial.
On the AWS side, it is very expensive because they charge based on query basis or how much data is transferred in and out, making it very expensive.
Having the hosted solution and not having to pay for essentially a DevOps person on staff to manage makes it affordable.
You can host it on-premises, which would incur zero cost, or take it as a SaaS-based service, where the expenses remain minimal.
It ranges from a quarter million to a couple of million a year.
Informatica Intelligent Cloud Services is affordable for my specific use cases, with the pricing being rated three or four on a scale where one is very cheap.
Regarding pricing, compared to other tools I have worked with, Informatica offers competitive pricing, which I find not high in terms of starting strategy.
Elastic Search makes handling large data volumes efficient and supports complex search operations.
The most valuable feature of Elasticsearch was the quick search capability, allowing us to search by any criteria needed.
The speed with which Elastic Search is able to search through all of the documents we place into it is quite remarkable, as we search through 65 billion documents in less than a second in most cases, on a constant consistent basis.
The platform's ability to pull in data from other platforms without the need for an additional integration tool enhances its appeal.
The connectors serve as the main functionality, making data integration processes more efficient by saving time and effort.
We could run data quality rules as part of Service Bus, which ensured the integrity of customer information before it was entered into our database.
| Product | Market Share (%) |
|---|---|
| Informatica Intelligent Data Management Cloud (IDMC) | 6.7% |
| Elastic Search | 1.6% |
| Other | 91.7% |


| Company Size | Count |
|---|---|
| Small Business | 37 |
| Midsize Enterprise | 10 |
| Large Enterprise | 43 |
| Company Size | Count |
|---|---|
| Small Business | 51 |
| Midsize Enterprise | 27 |
| Large Enterprise | 153 |
Elasticsearch is a prominent open-source search and analytics engine known for its scalability, reliability, and straightforward management. It's a favored choice among enterprises for real-time data search, analysis, and visualization. Open-source Elasticsearch is free, offering a comprehensive feature set and scalability. It allows full control over deployments but requires managing and maintaining the infrastructure. On the other hand, Elastic Cloud provides a managed service with features like automated provisioning, high availability, security, and global reach.
Elasticsearch excels in handling time-sensitive data and complex search requirements across large datasets. Its scalability allows it to handle growing data volumes efficiently, maintaining high performance and fast response times. Integrated with Kibana, Elasticsearch enables powerful data visualization, providing real-time insights crucial for data-driven decision-making.
Elastic Cloud reduces operational overhead and improves scalability and performance, though it comes with associated costs. It is available on your preferred cloud provider — AWS, Azure, or Google Cloud. Customers who want to manage the software themselves, whether on public, private, or hybrid cloud, can download the Elastic Stack.
At its core, Elasticsearch is renowned for its full-text search capabilities, capable of performing complex queries and supporting features like fuzzy matching and auto-complete.
Peer reviews from various professionals highlight its strengths and weaknesses. Pros include its detection and correlation features, flexibility, cloud-readiness, extensibility, and efficient search capabilities. However, users have noted challenges like steep learning curves, data analysis limitations, and integration complexities. The platform is generally viewed as stable and scalable, with varying degrees of satisfaction regarding its usability and feature set.
In summary, Elasticsearch stands out for its high-speed search, scalability, and versatile analytics, making it a go-to solution for organizations managing large datasets. Its adaptability to different enterprise needs, robust community support, and continuous development keep it at the forefront of enterprise search and analytics solutions. However, potential users should be aware of its learning curve and the need for skilled personnel for optimization.
Informatica Intelligent Data Management Cloud (IDMC) offers seamless integration of master data management, data quality, and data integration with a cloud-native architecture supporting multiple data management styles, optimizing data governance through metadata management.
IDMC enhances data synchronization and mapping tasks, utilizing a broad range of connectors to interact efficiently with data sources. Its precise address validation via AddressDoctor and intuitive navigation bolster user empowerment, delivering agility, scalability, and security in data governance. Despite its strengths, areas like ease of use, SAP integration, and reporting could benefit from enhancements. Connectivity issues and workflow complexities are noted, needing improvements in performance, support, and licensing cost. Users demand expanded ETL capabilities, real-time processing, and broader data source support to address growing data needs.
What are the key features of IDMC?In industries such as banking, healthcare, and telecom, IDMC is implemented for data integration, cloud migration, and enhancing data quality. Its capabilities are crucial for metadata management, lineage tracking, and real-time processing, ensuring high data quality and streamlined operations.
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