Qrvey VS Amazon Elasticsearch Service
Compare Qrvey VS Amazon Elasticsearch Service and see what are their differences
User onboarding made easy, for less. Create product walkthroughs in a couple of clicks, without breaking the bank.
featured
Qrvey
DevicePilot
AnswerRocket
Syndigo
Amdocs CES
Yellowfin
Omniscope
Toucan Toco
Amazon Elasticsearch Service
Amazon Kinesis
PieSync
TIBCO Spotfire
ElasticSearch
Kibana
Apache Flink
Algolia
Designed for external use cases where SaaS companies need to provide their customers with powerful and customizable analytics capabilities.
Qrvey is the only full stack solution that offers all the embedded visualization and self-service analytics tools along with a unified data pipeline that offers a data lake optimized for multi-tenant analytics.
Qrvey's embedded visualizations empower engineering teams to build custom experiences, along with full white labeling and CSS customization options to make Qrvey’s javascript widgets blend seamlessly into a SaaS application. ⋅⋅* Qrvey’s data-driven automation workflows enable the creation of complex workflows based on data triggers, such as conditional logic, nested functions, data write-backs with notification integrations to third party systems such as Slack. ⋅⋅* Qrvey supports natural language querying of data using generative AI to easily spot trends and outliers, augmented analysis capabilities. ⋅⋅* Qrvey also supports pixel perfect reporting to generate printable reports from the same analytics data.
Qrvey simplifies data management by providing a single data pipeline solution featuring a data lake solution that is optimized for multi-tenant analytics. This contains native data connectors and APIs to ingest data in any type from any source, including real-time data with live connections. ⋅⋅* Qrvey’s semantic layer can inherit and map security models from your multi-tenant SaaS application, saving software development teams the hassle of duplicating users and roles. ⋅⋅* Qrvey’s robust API allows you to create data delivery services and managed download functions that go beyond basic exporting.
Qrvey Amazon Elasticsearch ServiceNo features have been listed yet.
Qrvey's answer
Product Leaders that include Product Management and Engineering Teams and CEO/CTO/CPOs of B2B SaaS Companies
Qrvey's answer
Customers choose Qrvey for the following reasons:
Qrvey's answer
Qrvey's approach to embedded analytics is different. Qrvey combines the best of BI, data warehousing, and data visualization into a single solution built exclusively for SaaS applications.
Qrvey's key features include:
100% Embeddability - Everything is embeddable with JS based components that supports full white labeling so you can create unique analytics experiences within your SaaS application.
Data Warehouse included - Visualizations are useless without a scalable data layer built specifically for analytics use cases. Qrvey includes native multi-tenant support so your data is ready for your multi-tenant SaaS application. This includes data syncing and API support that allows for any type of data to be ingested into the Qrvey data layer.
Self-Hosted - Deployed to Your AWS Environment. Customers get ultimate control as Qrvey is deployed to their AWS environment inheriting and respecting their security policies. Your data never leaves, but it's ready for analytics now.
Based on our record, Amazon Elasticsearch Service seems to be a lot more popular than Qrvey. While we know about 11 links to Amazon Elasticsearch Service, we've tracked only 1 mention of Qrvey. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Since you're on AWS already, check out https://qrvey.com. Source: 6 months ago
This change triggered a response from Amazon Web Services, which offered OpenSearch (data store and search engine) and OpenSearch Dashboards (visualization and user interface) as Apache2.0 licensed open-source projects. - Source: dev.to / 3 months ago
Amazon OpenSearch Service allows you to deploy a secured OpenSearch cluster in minutes. - Source: dev.to / 10 months ago
If yes to these, then OpenSearch is where you are looking. I rarely ever use OpenSearch on its own but usually pair it with DynamoDB. The performance of DDB and the power of searching with OpenSearch make a nice combination. And as with most things with Serverless, pick the right tool for the job. And when it comes to Data, there are so many choices because each one of these is specific to the problem it solves. - Source: dev.to / 10 months ago
Have you looked into Amazon OpenSearch Service (https://aws.amazon.com/opensearch-service/)? You should be able to load the log files into that service and then query it there. Should simplify things a lot. Source: about 1 year ago
Elasticsearch (analytics) An open-source, real-time distributed search and analytics engine used for full-text search, structured search, and analytics. OpenSearch was developed by the Elastic company. Amazon OpenSearch Service (OpenSearch Service) is an AWS-managed service for deploying, operating and scaling OpenSearch in the AWS Cloud. Https://aws.amazon.com/opensearch-service/. - Source: dev.to / over 1 year ago
DevicePilot - DevicePilot is a universal cloud-based software service allowing you to easily locate, monitor and manage your connected devices at scale.
Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
AnswerRocket - AnswerRocket is a search-powered analytics that makes it possible to get answers from business data by asking natural language questions.
PieSync - Seamless two-way sync between your CRM, marketing apps and Google in no time
Syndigo - Syndigo is an online management platform that provides access to the world’s biggest global content database of digital information.
TIBCO Spotfire - TIBCO Spotfire is a Business Intelligence (BI) solution that provides users with executive dashboards, data visualization, data analytics and KPIs push to mobile devices.