

Find out in this report how the two Cloud Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
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.
I conducted a cost comparison with the AWS service provider, and this option is much cheaper than the Kinesis service offered by AWS.
Customers have seen ROI with Qlik Replicate because they get their data for analysis faster, enabling quicker decision-making compared to traditional data sourcing methods.
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.
Even priority tickets, which should be resolved in minutes, can take days.
Support response times could be improved as there are sometimes delays in receiving replies to support cases.
Having a technical account manager coordinate with us proved beneficial during these interactions.
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.
The system could be scaled to include more sources and functions.
We successfully scaled several of our Oracle RDBMS systems simultaneously, including PeopleSoft HR and our network access request systems.
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.
We have tracked INSERT, UPDATE, and DELETE operations effectively, capturing pre-update and post-update images, maintaining real-time replicas of information without needing to reprocess requests or datasets.
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.
It is a core-based licensing, which, especially in the banking industry, results in the system capacity being utilized up to a maximum of 60%.
I believe that having updated documentation is crucial as we encountered a scenario while going through documentation that had not been updated since 2024, which introduced risks since we rely on accurate documentation for task imports and endpoint re-credentialing considerations before reaching out to customer support.
Qlik Replicate could be improved in the next release by incorporating more monitoring options to monitor the logs.
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.
Licensing is calculated based on the machine's total capacity rather than actual usage.
For Qlik Replicate, the setup cost includes the requirement of a server, which represents the hardware cost that must be covered.
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 most valuable feature of Qlik Replicate is their change data capture feature.
The log-based CDC engine of Qlik Replicate is the most valuable feature for us. It reads our source changes directly from the database log, providing a lightweight approach that ensures our databases, such as Oracle databases, are not burdened with additional queries.
Data retrieved from the system can be pushed to multiple places, supporting various divisions such as marketing, loans, and others.

| Company Size | Count |
|---|---|
| Small Business | 37 |
| Midsize Enterprise | 10 |
| Large Enterprise | 43 |
| Company Size | Count |
|---|---|
| Small Business | 9 |
| Large Enterprise | 11 |
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.
Qlik Replicate is a data replication solution for replicating data from one source database to another for business intelligence software. It offers data manipulation and transformations, replication without impacting source databases, and ease of use without needing ETL. The solution is stable and user-friendly, with detailed logging and support.
Qlik Replicate has improved the organization by allowing each team to replicate their data into a single-source data location. The most important feature of Qlik Replicate is its ability to replicate and update records without needing a programmer.
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