Elastic Search and Fivetran compete in the data analytics and integration space. Elastic Search appears to have the upper hand in analytics due to its advanced search capabilities and comprehensive data visualization.
Features: Elastic Search offers efficient search capabilities, extensive integrations via ELK, and AI-driven insights, coupled with visualization tools like Kibana. Its open-source nature supports customization. Fivetran excels with managed data integration pipelines, providing a user-friendly experience with a multitude of connectors and seamless ETL processes.
Room for Improvement: Elastic Search can enhance its security in the free version and simplify its UI for non-technical users. Users express a need for better documentation and alert functionalities. Fivetran faces criticism for high costs and limited real-time integrations, in addition to demands for more connectors and enhanced reverse ETL capabilities.
Ease of Deployment and Customer Service: Elastic Search offers versatility with on-premises and cloud deployments but relies on community support without paid packages. Its strong user community aids users. Fivetran is optimized for public cloud deployments, providing responsive but costly support services. Its structured technical service with clear SLAs is beneficial for customers.
Pricing and ROI: Elastic Search's free open-source model allows cost-effective deployment but incurs backend costs for maintenance and premium features. Its ROI is significant with effective implementation. Fivetran charges based on data integration volume, scaling for large datasets but costly for small volumes. It lacks a free tier, reflecting a commercial orientation.
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.
It saves us the effort of having one to two data engineers managing the tasks that Fivetran handles.
The technical support provided by Fivetran has generally been good, with a response time and competence that I would rate as good.
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.
The data transfer sometimes exceeded the bandwidth limits without proper notification, which caused issues.
It was consistent and reliable in our usage.
During the duration of the time that we used Fivetran, it was highly stable.
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.
It is primarily based on Unix or Linux-based operating systems and cannot be easily configured in Windows systems.
From a cost perspective, if the number of connectors is lesser, then Fivetran is not the most cost-efficient option.
Fivetran could improve by adapting more for technical users and by providing more options for such users.
We used the open-source version of Elasticsearch, which was free.
Our current yearly contract for Fivetran is approximately $70,000.
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.
Configuring Elasticsearch is much easier compared to comprehending other SIEM tools like Splunk.
The most valuable feature of Fivetran is its built-in connectors for a wide range of data sources.
The ability to seamlessly integrate with a large variety of data sources is valuable.
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.
Fivetran, the global leader in data movement, is trusted by companies like OpenAI, LVMH, Pfizer, Verizon and Spotify to centralize data from SaaS applications, databases, files, and other sources into cloud destinations, including data lakes. With high-performance pipelines, seamless interoperability, and enterprise-grade security, Fivetran empowers organizations to modernize their data infrastructure, power analytics and AI, ensure compliance, and achieve transformative business outcomes. Learn more at Fivetran.com
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