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SQream VS Google Cloud Dataflow

Compare SQream VS Google Cloud Dataflow and see what are their differences

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SQream logo SQream

SQream empowers organizations to analyze the full scope of their Massive Data, from terabytes to petabytes, to achieve critical insights which were previously unattainable.

Google Cloud Dataflow logo Google Cloud Dataflow

Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
  • SQream Landing page
    Landing page //
    2023-09-17

SQream is a data analytics acceleration platform built especially for massive data - from terabytes to petabytes. SQream takes queries down from days to hours and hours to minutes. The SQream platform provides the ability to analyze more data, faster, with multiple dimensions and cuts data preparation significantly by enabling ad-hoc querying on raw data. Leading global organizations in telecommunications, healthcare, ad-tech, retail and more rely on SQream to achieve critical business insights and potentially valuable BI across their massive data stores.

  • Google Cloud Dataflow Landing page
    Landing page //
    2023-10-03

SQream videos

+ Add

SQream DB v2020.1 - Product review and demo

More videos:

  • Review - Introducing SQream DB - The GPU-accelerated data warehouse for massive data
  • Review - SQream DB, GPU-accelerated data warehouse

Google Cloud Dataflow videos

+ Add

Introduction to Google Cloud Dataflow - Course Introduction

More videos:

  • Review - Serverless data processing with Google Cloud Dataflow (Google Cloud Next '17)
  • Review - Apache Beam and Google Cloud Dataflow

Category Popularity

0-100% (relative to SQream and Google Cloud Dataflow)

SQream

Google Cloud Dataflow

Data Dashboard
8 8%
Data Dashboard
92% 92
Big Data
6 6%
Big Data
94% 94
Big Data Infrastructure
100 100%
Big Data Infrastructure
0% 0
Data Warehousing
0 0%
Data Warehousing
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare SQream and Google Cloud Dataflow

SQream Reviews

We have no reviews of SQream yet.
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Google Cloud Dataflow Reviews

Top 8 Apache Airflow Alternatives in 2024
Google Cloud Dataflow is highly focused on real-time streaming data and batch data processing from web resources, IoT devices, etc. Data gets cleansed and filtered as Dataflow implements Apache Beam to simplify large-scale data processing. Such prepared data is ready for analysis for Google BigQuery or other analytics tools for prediction, personalization, and other purposes.
Source: blog.skyvia.com

Social recommendations and mentions

Based on our record, Google Cloud Dataflow seems to be a lot more popular than SQream. While we know about 14 links to Google Cloud Dataflow, we've tracked only 1 mention of SQream. 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.

SQream mentions (1)

Google Cloud Dataflow mentions (14)

  • How do you implement CDC in your organization
    Imo if you are using the cloud and not doing anything particularly fancy the native tooling is good enough. For AWS that is DMS (for RDBMS) and Kinesis/Lamba (for streams). Google has Data Fusion and Dataflow . Azure hasData Factory if you are unfortunate enough to have to use SQL Server or Azure. Imo the vendored tools and open source tools are more useful when you need to ingest data from SaaS platforms, and... Source: over 1 year ago
  • Here’s a playlist of 7 hours of music I use to focus when I’m coding/developing. Post yours as well if you also have one!
    This sub is for Apache Beam and Google Cloud Dataflow as the sidebar suggests. Source: over 1 year ago
  • How are view/listen counts rolled up on something like Spotify/YouTube?
    I am pretty sure they are using pub/sub with probably a Dataflow pipeline to process all that data. Source: over 1 year ago
  • Best way to export several GCP datasets to AWS?
    You can run a Dataflow job that copies the data directly from BQ into S3, though you'll have to run a job per table. This can be somewhat expensive to do. Source: over 1 year ago
  • Why we don’t use Spark
    It was clear we needed something that was built specifically for our big-data SaaS requirements. Dataflow was our first idea, as the service is fully managed, highly scalable, fairly reliable and has a unified model for streaming & batch workloads. Sadly, the cost of this service was quite large. Secondly, at that moment in time, the service only accepted Java implementations, of which we had little knowledge... - Source: dev.to / almost 2 years ago
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What are some alternatives?

When comparing SQream and Google Cloud Dataflow, you can also consider the following products

GridGain In-Memory Data Fabric - TheGridGain In-Memory Computing Platform is a comprehensive solution provides speed and scale for data intensive applications across any data store

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Panoply - Panoply is a smart cloud data warehouse

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

Apache ORC - Apache ORC is a columnar storage for Hadoop workloads.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

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