

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.
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.
Fivetran provides time savings, cost reductions, and improvements in data quality.
It saves us the effort of having one to two data engineers managing the tasks that Fivetran handles.
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.
If they could provide support more quickly, that would be great.
The technical support provided by Fivetran has generally been good, with a response time and competence that I would rate as good.
Customer support from Fivetran is quite good; it's really nice and responsive.
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.
Fivetran's scalability has been tested effectively, and it has been working well for our organization's growing data needs.
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.
They have 99.9% accuracy on the data load and they maintain transparency.
In my experience, Fivetran is stable with very few instances of downtime or reliability issues.
During the duration of the time that we used Fivetran, it was highly stable.
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.
From a cost perspective, if the number of connectors is lesser, then Fivetran is not the most cost-efficient option.
I want more flexibility during ingestion, specifically for transformations needed beforehand.
Fivetran could improve by adapting more for technical users and by providing more options for such users.
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.
Our current yearly contract for Fivetran is approximately $70,000.
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 Fivetran is its built-in connectors for a wide range of data sources.
The real-time data replication is what I see best in the market where it reduces the overhead of customers needing to maintain the pipeline.
The ability to seamlessly integrate with a large variety of data sources is valuable.
| Product | Market Share (%) |
|---|---|
| Elastic Search | 1.6% |
| Fivetran | 4.5% |
| Other | 93.9% |


| Company Size | Count |
|---|---|
| Small Business | 37 |
| Midsize Enterprise | 10 |
| Large Enterprise | 43 |
| Company Size | Count |
|---|---|
| Small Business | 10 |
| Midsize Enterprise | 7 |
| Large Enterprise | 16 |
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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