Amazon Kinesis
Apache Flink
Confluent
Apache Kafka
PieSync
Azure Stream Analytics
Spark Streaming
Google Cloud Dataflow
Google BigQuery
Databricks
Looker
Jupyter
Presto DB
Google Cloud Dataflow
Amazon EMR
Rakam
Amazon Kinesis Google BigQueryNo Google BigQuery videos yet. You could help us improve this page by suggesting one.
Based on our record, Google BigQuery should be more popular than Amazon Kinesis. It has been mentiond 35 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.
When you see Amazon Kinesis as an option, this becomes the ideal option to process data in real time. Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit... - Source: dev.to / about 2 months ago
RisingWave is an open-source streaming database that has built-in fully-managed CDC source connectors for various databases, also it can collect data from other sources such Kafka, Pulsar, Kinesis, or Redpanda and it allows you to query real-time streams using SQL. You can get a materialized view that is always up-to-date. - Source: dev.to / about 1 year ago
For example, RisingWave is one of the fastest-growing open-source streaming databases that can ingest data from Apache Kafka, Apache Pulsar, Amazon Kinesis, Redpanda, and databases via native Change data capture connections or using Debezium connectors to MySQL and PostgreSQL sources. Previously, I wrote a blog post about how to choose the right streaming database that discusses some key factors that you should... - Source: dev.to / about 1 year ago
RisingWave is an open-source distributed SQL database for stream processing. RisingWave accepts data from sources like Apache Kafka, Apache Pulsar, Amazon Kinesis, Redpanda, and databases via native Change data capture connections to MySQL and PostgreSQL sources. It uses the concept of materialized view that involves caching the outcome of your query operations and it is quite efficient for long-running stream... - Source: dev.to / about 1 year ago
You can ingest data from different data sources such as message brokers Kafka, Redpanda, Kinesis, Pulsar, or databases MySQL or PostgreSQL using their Change Data Capture (CDC) which is the process of identifying and capturing data changes. - Source: dev.to / about 1 year ago
Using the Galaxy UI, knowledge workers can systematically review the best results from all configured services including Apache Solr, ChatGPT, Elastic, OpenSearch, PostgreSQL, Google BigQuery, plus generic HTTP/GET/POST with configurations for premium services like Google's Programmable Search Engine, Miro and Northern Light Research. - Source: dev.to / 8 months ago
Data Transformations: This phase involves modifying and integrating tables to generate new tables optimized for analytical use. Consider this example: you want to understand the purchasing behavior of customers aged between 20-30 in your online shop. This means you'll need to join product, customer, and transaction data to create a unified table for analytics. These data preparation tasks (e.g., joining... - Source: dev.to / 8 months ago
Introduction In today's data-driven world, transforming raw data into valuable insights is crucial. This process, however, often involves complex tasks that demand efficiency, scalability, and reliability. Enter dbt Cloud—a powerful tool that simplifies data transformations on Google BigQuery. In this article, we'll take you through a step-by-step guide on how to run BigQuery transformations using dbt Cloud.... - Source: dev.to / 9 months ago
You'll want to evaluate what BigQuery has to offer and see if it makes sense for you to move over. Source: 10 months ago
Watch the introductory videos on BigQuery on the Google Cloud Platform website (https://cloud.google.com/bigquery). Source: 10 months ago
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?
Confluent - Confluent offers a real-time data platform built around Apache Kafka.
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
