Denodo and Elastic Search compete in the data management category, focusing on virtualization and integration versus search and log management, respectively. Denodo presents an edge in data virtualization with its comprehensive integration capabilities, while Elastic Search outperforms in scalability and search functionalities.
Features: Denodo excels in data virtualization and integration, highly valued for performance and ease of use in complex environments. Its data catalog supports diverse data sources with robust query optimization. Elastic Search offers outstanding search and log management capabilities with scalability and extensibility, providing high-performance text-based searches across various data types.
Room for Improvement: Denodo's data catalog needs a user-friendly interface and enhanced integration with data semantics. Better training materials and documentation could enhance user experience. Elastic Search requires better alerting features and improved machine learning capabilities. Simplifying certain component configurations and scalability on large data sets would benefit initial deployment experiences.
Ease of Deployment and Customer Service: Both Denodo and Elastic Search allow flexible deployment options across on-premises, public, and hybrid cloud setups. Denodo may require more technical support and better documentation from customers, while Elastic Search's community support is strong, though technical expertise is sometimes necessary for optimal deployment and configuration. Denodo's customer service may experience support delays, while Elastic Search offers consistent support through community resources.
Pricing and ROI: Denodo is expensive but often offers significant ROI within six months, with costs tied to CPU usage and connector fees. Elastic Search provides a free open-source version, incurring costs related to technical expertise for deployment and support. Its enterprise features position its cost at par with similar solutions, offering a flexible model considered cost-effective compared to alternatives like Splunk.
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.
We have not purchased any licensed products, and our use of Elastic Search is purely open-source, contributing positively to our ROI.
The documentation is very thorough.
Denodo's customer support team is very competent and responsive.
They are proactive in conducting webinars and connecting with customers.
I would rate technical support from Elastic Search as three out of ten.
Its complexity in configuring and the requirement to install different connectors for different sources affects its scalability.
While the solution scales well on a single machine, I have doubts about its scalability when deployed as part of a Java component cluster.
I would rate its scalability a ten.
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.
I would rate it nine out of ten because it is very reliable, always performing as expected.
If JVM does not function properly, it may cause Denodo to fail to connect to different sources.
The stability of Elasticsearch was very high.
The data transfer sometimes exceeded the bandwidth limits without proper notification, which caused issues.
Ensuring data caching is up to date is critical.
Denodo needs better communication on how the product can be deployed for specific solutions.
The system has dependencies on other environments, like JVM, which can affect its performance.
This can create problems for new developers because they have to quickly switch to another version.
The consistency and stability of Elasticsearch are commendable, and they should keep up the good work.
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.
Denodo's pricing is not affordable for small companies and is more suitable for medium to large enterprises.
Denodo is considered pricey, limiting its use to large enterprises or government organizations that can afford its comprehensive setup.
We used the open-source version of Elasticsearch, which was free.
Denodo's ability to connect to multiple data sources and perform extract-transform-load (ETL) operations on the fly is noteworthy.
The most valuable feature of Denodo is its uniformity of self-site data access types, which allows it to connect to almost any storage technology and feed it transparently.
Denodo is also effective for developing solutions quickly, facilitating user reports, and offering good data governance.
The most valuable feature of Elasticsearch was the quick search capability, allowing us to search by any criteria needed.
Elastic Search makes handling large data volumes efficient and supports complex search operations.
The full text search capabilities are particularly beneficial for handling large volumes of data.
Denodo is a leading data integration, management, and delivery platform that uses a logical approach to enable data science, hybrid and multi-cloud data integration, self-service BI, and enterprise data services. Organizations of different sizes across various industries utilize the product to get above the data silos. The solution offers organizations the freedom to migrate data to the cloud, or logically unify data warehouses and data lakes, without affecting business. This can ultimately result in the evolution of data strategies.
The platform accelerates data provisioning through reduced data replication, provides business users the freedom to select their preferred applications, and enables consistent security and governance across multiple systems. The solution offers one of the leading logical data fabric solutions by initiating data virtualization and eliminating the complexity and exposing the data in business-friendly formats.
Denodo also offers modern data integration and management for hybrid and multi-cloud environments for Denodo Platform for Cloud. This service can be purchased through the bring-your-own-license (BYOL) option. Users seeking faster deployment can license the product to popular cloud providers, including Amazon AWS, Google Cloud Platform, and Microsoft Azure. The solution integrates, manages, and delivers data in complex environments with high performance, governance, and security. It also offers additional solutions, such as the Denodo Platform for Cloud Modernization, the Denodo Platform for Cloud Data Integration, and the Denodo Platform for Cloud Analytics, which overcome common cloud data challenges.
Denodo Features
At the beginning of 2022, version 8.0 of Denodo introduced several new key features of the platform. These include:
Denodo Benefits
Denodo offers various benefits for its users through its services. Some of the greatest advantages of using this platform include:
Reviews from Real Users
Naresh M., a senior application developer at a financial services firm, appreciates Denodo because it offers quick and simple web services creation.
Alisson M., a senior BigData DevOps engineer at Schaeffler, says that Denodo is great for queries and scouting data.
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.
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