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Apache Beam VS Qrvey

Compare Apache Beam VS Qrvey and see what are their differences

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Contents:
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  2. » Videos
  3. » Reviews
  4. » Alternatives

Apache Beam logo Apache Beam

Apache Beam provides an advanced unified programming model to implement batch and streaming data processing jobs.

Qrvey logo Qrvey

Embedded Analytics built exclusively for SaaS applications.
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  • Apache Beam Landing page
    Landing page //
    2022-03-31
  • Qrvey Landing page
    Landing page //
    2023-11-21
  • Qrvey
    Image date //
    2024-05-20
  • Qrvey
    Image date //
    2024-05-20

Qrvey is the only purpose-built solution for embedded analytics

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:

  • Elasticsearch as the analytics engine
  • A unified data pipeline for ingestion and transformation
  • A complete semantic layer for simple user and data security integration

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.

Apache Beam features and specs

No features have been listed yet.

Qrvey features and specs

  • Embedded Dashboards: Yes
  • Embedded Dashboard Builders: Yes
  • Embedded Single Charts/Metrics: Yes
  • Embedded Single Chart/Metric Builder: Yes
  • Data Warehouse: Yes
  • ETL: Yes
  • Alerts and Automation: Yes
  • Embedded Pixel-Perfect Reports: Yes
  • Native Multi-Tenant Data Security: Yes
  • Tenant Specific Content Deployment: Yes
  • Prebuilt Data Connectors (Redshift, PostgreSQL, Snowflake, etc): Yes

Apache Beam videos

+ Add

How to Write Batch or Streaming Data Pipelines with Apache Beam in 15 mins with James Malone

More videos:

  • Review - Best practices towards a production-ready pipeline with Apache Beam
  • Review - Streaming data into Apache Beam with Kafka

Qrvey videos

+ Add

Qrvey Embedded Analytics Demo

More videos:

  • Demo - Qrvey Intro Video

Category Popularity

0-100% (relative to Apache Beam and Qrvey)

Apache Beam

Qrvey

Big Data
100 100%
Big Data
0% 0
Data Dashboard
19 19%
Data Dashboard
81% 81
Business Intelligence
0 0%
Business Intelligence
100% 100
Data Warehousing
100 100%
Data Warehousing
0% 0

Questions and Answers

As answered by people managing Apache Beam and Qrvey.

How would you describe your primary audience?

Qrvey's answer:

Product Leaders that include Product Management and Engineering Teams and CEO/CTO/CPOs of B2B SaaS Companies

What makes your product unique?

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:

  • Everything is a JS embed, no iFrames
  • Dashboards and builders
  • Dataset creation for individual users
  • No-code workflow automation
  • Full white-labeling and CSS support

All of this is backed by a semantic layer that makes integrating Qrvey into the security model of SaaS applications simple.

Why should a person choose your product over its competitors?

Qrvey's answer:

Customers choose Qrvey for the following reasons:

  • In-house engineering teams spend less time developing analytics features
  • Infrastructure costs are significantly less
  • Engineering teams get JS embeds and a richer API suite than anyone else
  • Fully customizable to blend in seamlessly with the parent SaaS application

User comments

Share your experience with using Apache Beam and Qrvey. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Beam and Qrvey

Apache Beam Reviews

We have no reviews of Apache Beam yet.
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Qrvey Reviews

10 Best Big Data Analytics Tools For Reporting In 2022
Qrvey is an embedded analytics platform used for SaaS data, analytics, and automation technologies. You can deploy it right into your pre-existing AWS account in order to visualize your entire data pipeline. Their start-ups package includes specialized support for pre-launch or early-launch companies, like quick installation and launch, serverless analytics scalability,...
Source: theqalead.com
Top 5 Embedded Analytics Tools for Amazon Redshift (Plus 1 Bonus Option)
Qrvey is an embedded analytics and automation tool designed specifically for SaaS applications. It connects directly to AWS and offers an all-in-one platform that includes data collections, analysis, visualizations, automation, and more.
Source: yurbi.com

Social recommendations and mentions

Based on our record, Apache Beam seems to be a lot more popular than Qrvey. While we know about 14 links to Apache Beam, 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.

Apache Beam mentions (14)

  • Ask HN: Does (or why does) anyone use MapReduce anymore?
    The "streaming systems" book answers your question and more: https://www.oreilly.com/library/view/streaming-systems/9781491983867/. It gives you a history of how batch processing started with MapReduce, and how attempts at scaling by moving towards streaming systems gave us all the subsequent frameworks (Spark, Beam, etc.). As for the framework called MapReduce, it isn't used much, but its descendant... - Source: Hacker News / 5 months ago
  • How do Streaming Aggregation Pipelines work?
    Apache Beam is one of many tools that you can use. Source: 6 months ago
  • Real Time Data Infra Stack
    Apache Beam: Streaming framework which can be run on several runner such as Apache Flink and GCP Dataflow. - Source: dev.to / over 1 year ago
  • Google Cloud Reference
    Apache Beam: Batch/streaming data processing 🔗Link. - Source: dev.to / almost 2 years ago
  • Composer out of resources - "INFO Task exited with return code Negsignal.SIGKILL"
    What you are looking for is Dataflow. It can be a bit tricky to wrap your head around at first, but I highly suggest leaning into this technology for most of your data engineering needs. It's based on the open source Apache Beam framework that originated at Google. We use an internal version of this system at Google for virtually all of our pipeline tasks, from a few GB, to Exabyte scale systems -- it can do it all. Source: almost 2 years ago
View more

Qrvey mentions (1)

  • Looking for an embedded report builder solution that doesn't require giving a third-party access to the data
    Since you're on AWS already, check out https://qrvey.com. Source: 7 months ago

What are some alternatives?

When comparing Apache Beam and Qrvey, you can also consider the following products

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

DevicePilot - DevicePilot is a universal cloud-based software service allowing you to easily locate, monitor and manage your connected devices at scale.

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

Syndigo - Syndigo is an online management platform that provides access to the world’s biggest global content database of digital information.

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

AnswerRocket - AnswerRocket is a search-powered analytics that makes it possible to get answers from business data by asking natural language questions.

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