Snowflake
Google BigQuery
Amazon EMR
Databricks
Qubole
Amazon Redshift
Azure HDInsight
Google Cloud Dataflow
Apache Storm
Apache Spark
Apache Flink
Qubole
Apache Beam
Google BigQuery
Hadoop
Amazon Kinesis
Snowflake Apache StormBased on our record, Apache Storm should be more popular than Snowflake. It has been mentiond 11 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.
Snowflake, a data warehousing company founded by ex-Oracle and ex-VectorWise experts, responded with a blog post that critically reviewed Databricks' findings, reported different results for the same benchmark, and claimed comparable price/performance to Databricks. - Source: dev.to / almost 2 years ago
Snowflake: Snowflake is fast, and works well as a product analytics database. - Source: dev.to / over 2 years ago
If you just go to snowflake.com you can sign up for a demo account for free for a month and I'm fairly certain you can get more than one of these accounts (I would recycle emails doing it all the time.) Once you have an account there's lots of docs and videos out there either using the Database via their UI or via python using their connector. They also have a pyspark connector but you might want to just learn... Source: over 2 years ago
Early stage funding & VCs clearly demarcate between tech companies and tech enabled companies. But, once the PE comes into the picture at the scale of BlackStone, the border between doordash.com and snowflake.com starts to blur. The motivation is to make some bucks by going to IPO and they know how to get it done. Source: over 2 years ago
There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 1 year ago
Although this article lists a lot of targets for technical selection, there are definitely others that I haven't listed, which may be either outdated, less-used options such as Apache Storm or out of my radar from the beginning, like JAVA ecosystem. - Source: dev.to / over 1 year ago
Storm, a system for real-time and stream processing. - Source: dev.to / over 1 year ago
Google has scaled well and has helped others scale, Twitter has always been behind by years. I think the only thing they did well was Twitter Storm, now taken up by Apache Foundation. Source: over 1 year ago
Streaming: Sparks Streamings's latency is at least 500ms, since it operates on micro-batches of records, instead of processing one record at a time. Native streaming tools like Storm, Apex or Flink might be better for low-latency applications. - Source: dev.to / over 2 years ago
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.
