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Google Cloud Dataflow VS VeloDB

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

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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.

VeloDB logo VeloDB

Modern Real-Time Data Warehouse
  • Google Cloud Dataflow Landing page
    Landing page //
    2023-10-03
  • VeloDB VeloDB
    VeloDB //
    2024-01-10

VeloDB is a modern real-time data warehouse powered by open source Apache Doris for lightning-fast data analytics at scale. It ensures big data ingestion within seconds and outstanding performance in both real-time serving and interactive ad-hoc queries. It is one platform for various analytics workloads, including structured and semi-structured data processing, real-time analytics and batch processing, internal data query and federated queries of external data. It allows elastic scaling for efficient resource management. It can dynamically adjust the computing resources allocated to the workload based on the changing requirements. It supports MySQL protocol and standard SQL for easy integration with other data tools. It also provides open data API to be accessible for various external query engines.

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

VeloDB videos

No VeloDB videos yet. You could help us improve this page by suggesting one.

+ Add video

Category Popularity

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

Google Cloud Dataflow

VeloDB

Big Data
100 100%
Big Data
0% 0
Data Warehousing
76 76%
Data Warehousing
24% 24
Data Dashboard
100 100%
Data Dashboard
0% 0
Databases
0 0%
Databases
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 Google Cloud Dataflow and VeloDB

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

VeloDB Reviews

We have no reviews of VeloDB yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Google Cloud Dataflow seems to be more popular. It has been mentiond 14 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.

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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VeloDB mentions (0)

We have not tracked any mentions of VeloDB yet. Tracking of VeloDB recommendations started around Jan 2024.

What are some alternatives?

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

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

Snowflakepowe.red - Snowflake Computing is delivering a data warehouse for the cloud.

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

ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.

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

Presto - Next generation front-of-house technology

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