

SnapLogic and ElasticSearch compete in the technology landscape, focusing respectively on integration and automation versus search and analytics. ElasticSearch holds an edge due to its advanced features, despite SnapLogic's advantage in pricing and support.
Features: SnapLogic's strengths include an intuitive data integration platform, seamless cloud and on-premise connectivity, and advanced automation. ElasticSearch excels with a powerful search and analytics engine, offering speedy queries of large datasets, advanced data indexing, and full-text search features.
Room for Improvement: SnapLogic could enhance user interface customization, offer more detailed analytics reporting, and expand its real-time integration capabilities. ElasticSearch would benefit from streamlined deployment processes, enhanced ease of use for non-technical users, and improved integration with third-party services.
Ease of Deployment and Customer Service: SnapLogic provides straightforward cloud-based deployment with extensive support resources for quick setup and efficient troubleshooting. ElasticSearch requires technical expertise for deployment but offers vast community support and detailed documentation to guide proficient maintenance.
Pricing and ROI: SnapLogic is seen as a cost-effective solution, with lower immediate setup costs and a clear ROI path by enhancing integration efficiency. ElasticSearch, with higher initial costs, promises significant long-term ROI through superior data search and analysis capabilities, appealing to businesses focused on optimizing data-driven decisions.
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.
SnapLogic is really helpful and processes in very little time, so it doesn't take much time compared to any legacy tool.
SnapLogic has helped automate manual data transfers significantly and improved our workflow efficiency, reducing integration development timelines considerably, which reflects a good ROI.
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.
The technical support from SnapLogic is excellent, and I would give it a complete ten.
Some SMEs are allotted for the organization, so in case of any issue, we have their email IDs to contact them for support, including SMEs and community.
Customer support scales well; as pipeline volume grows, we have been able to add more integrations and users without performance degradation.
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.
I rate the scalability of SnapLogic as eight out of ten.
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.
I would rate the stability of SnapLogic as nearly ten out of ten.
But recently, in a year, I haven't found many performance issues in SnapLogic.
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.
If the AI capabilities and integrations were more intuitive and easy to learn for new users, it would be greatly beneficial.
They can improve more visuals, with graphical representations, such as how many things can be added, how many users can be added or dropped, and how the back-end nodes can be graphically shown in a better way.
I tend to frequently communicate with SnapLogic to ask for additional features, and they have been responsive.
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.
I would say the pricing is on the higher side, but it aligns with the capabilities offered for mid- to large integrations.
There would be only one point of improvement if the price could be lower.
SnapLogic is positioned at around seven or eight out of ten in terms of pricing.
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.
I also like the whole child-parent pipeline feature; it allows me to break up a process into smaller pieces and then have one big pipeline that controls these smaller pipelines.
The drag-and-drop builder and pre-built snaps have helped our team through a very low-code approach, making it easier for us to develop fast pipelines and be more agile compared to the heavier integration platforms we used before.
I find SnapLogic to be user-friendly, especially for beginners with limited experience in data engineering or ETL.
| Product | Market Share (%) |
|---|---|
| Elastic Search | 1.6% |
| SnapLogic | 3.0% |
| Other | 95.4% |


| Company Size | Count |
|---|---|
| Small Business | 37 |
| Midsize Enterprise | 10 |
| Large Enterprise | 43 |
| Company Size | Count |
|---|---|
| Small Business | 11 |
| Midsize Enterprise | 5 |
| 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.
The SnapLogic Intelligent Integration Platform uses AI-powered workflows to automate all stages of IT integration projects – design, development, deployment, and maintenance – whether on-premises, in the cloud, or in hybrid environments. The platform’s easy-to-use, self-service interface enables both expert and citizen integrators to manage all application integration, data integration, API management, B2B integration, and data engineering projects on a single, scalable platform. With SnapLogic, organizations can connect all of their enterprise systems quickly and easily to automate business processes, accelerate analytics, and drive transformation.
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