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.
It is stable, and we do not encounter critical issues like server downtime, which could result in data loss.
We have not purchased any licensed products, and our use of Elastic Search is purely open-source, contributing positively to our ROI.
I conducted a cost comparison with the AWS service provider, and this option is much cheaper than the Kinesis service offered by AWS.
Even priority tickets, which should be resolved in minutes, can take days.
I would rate the scalability of Elasticsearch as an eight.
I can actually add more storage and memory because I host it in the cloud.
The data transfer sometimes exceeded the bandwidth limits without proper notification, which caused issues.
This can create problems for new developers because they have to quickly switch to another version.
It is primarily based on Unix or Linux-based operating systems and cannot be easily configured in Windows systems.
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%.
Licensing is calculated based on the machine's total capacity rather than actual usage.
Elastic Search makes handling large data volumes efficient and supports complex search operations.
Aggregation is faster than querying directly from a database, like Postgres or Vertica.
Configuring Elasticsearch is much easier compared to comprehending other SIEM tools like Splunk.
Data retrieved from the system can be pushed to multiple places, supporting various divisions such as marketing, loans, and others.
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.
We monitor all Cloud Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.