JanusGraph
neo4j
ArangoDB
Apache TinkerPop
OrientDB
RedisGraph
Redis
MongoDB
Qrvey
DevicePilot
AnswerRocket
Syndigo
Amdocs CES
Yellowfin
Toucan Toco
Omniscope
Qrvey is the only solution for embedded analytics with a built-in data lake. Qrvey saves engineering teams time and money with a turnkey solution connecting your data warehouse to your SaaS application.
Qrvey’s full-stack solution includes the necessary components so that your engineering team can build less.
Qrvey’s multi-tenant data lake includes:
Qrvey’s embedded visualizations support everything from: - Standard dashboards and templates - Self-service reporting - User-level personalization - Individual dataset creation - Data-driven workflow automation
Qrvey delivers this as a self-hosted package for cloud environments. This offers the best security as your data never leaves your environment while offering a better analytics experience to users.
The result: Less time and money on analytics.
JanusGraph QrveyNo 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:
Qrvey takes a different approach to embedded analytics. Instead of focusing almost completely on the front end, we know that any analytics function starts with data.
Qrvey includes a full-featured data lake powered by Elasticsearch, not a basic relational caching layer. Furthermore, by including a data lake, the cost to scale out is much less than traditional data warehouses.
For the user-facing components of the platform, Qrvey offers more embedded components and APIs to personalize the experience beyond static dashboards. Qrvey offers:
All of this is backed by a semantic layer that makes integrating Qrvey into the security model of SaaS applications simple.
Qrvey's answer:
Customers choose Qrvey for the following reasons:
Based on our record, JanusGraph should be more popular than Qrvey. It has been mentiond 2 times since March 2021. 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.
First, you need to choose a specific graph database platform to work with, such as Neo4j, OrientDB, JanusGraph, Arangodb or Amazon Neptune. Once you have selected a platform, you can then start working with graph data using the platform's query language. - Source: dev.to / about 1 year ago
QOMPLX partnered with the graph database experts at Expero to implement their system with JanusGraph, which uses Scylla as an underlying fast and scalable storage layer. We had the privilege to learn from their use case at Scylla Summit this January, which we share with you today. Source: about 3 years ago
Since you're on AWS already, check out https://qrvey.com. Source: 6 months ago
neo4j - Meet Neo4j: The graph database platform powering today's mission-critical enterprise applications, including artificial intelligence, fraud detection and recommendations.
DevicePilot - DevicePilot is a universal cloud-based software service allowing you to easily locate, monitor and manage your connected devices at scale.
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.
AnswerRocket - AnswerRocket is a search-powered analytics that makes it possible to get answers from business data by asking natural language questions.
Apache TinkerPop - Apache TinkerPop is a graph computing framework for both graph databases (OLTP) and graph analytic systems (OLAP).
Syndigo - Syndigo is an online management platform that provides access to the world’s biggest global content database of digital information.
