Software Alternatives & Reviews

Amazon Redshift Reviews

Learn about Amazon Redshift cloud data warehouse.

Social recommendations and mentions

We have tracked the following product recommendations or mentions on Reddit and HackerNews. They can help you see what people think about Amazon Redshift and what they use it for.
  • AWS Beginner's Key Terminologies
    Amazon Redshift (analytics) Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. With Amazon Redshift, you can analyze your data using your existing business intelligence tools. Https:// - Source: / 2 months ago
  • How to build your own data platform. Episode 1: sharing data between environments. Data Warehouse implementation.
    Data Warehouse: many times you will need to implement star schemas for creating data marts. Here, users can find meaningful data for creating dashboards, machine learning products or any other thing that users require. In this case, the Data Warehouse will be implemented on AWS Redshift. - Source: / 4 months ago
  • Deploying a Data Warehouse with Pulumi and Amazon Redshift
    A data warehouse is a specialized database that's purpose built for gathering and analyzing data. Unlike general-purpose databases like MySQL or PostgreSQL, which are designed to meet the real-time performance and transactional needs of applications, a data warehouse is designed to collect and process the data produced by those applications, collectively and over time, to help you gain insight from it. Examples of... - Source: / 4 months ago
  • Apache Kafka Use Cases: When To Use It & When Not To
    A Kafka-based data integration platform will be a good fit here. The services can add events to different topics in a broker whenever there is a data update. Kafka consumers corresponding to each of the services can monitor these topics and make updates to the data in real-time. It is also possible to create a unified data store through the same integration platform. Developers can implement a unified store either... - Source: / 7 months ago
  • Swipe Right on Redshift
    His keen sense of smell indicated this was a too much/big data problem. He suggested instead of running the query against PostgreSQL, we run it instead against Amazon Redshift, which the Data team already uses for similar data pipelines. - Source: / 7 months ago
  • 3 Tools to Manage Data Warehouse Concurrency
    Amazon Redshift is a petabyte-scale cloud data warehouse platform for storing and analyzing large data sets that are completely managed. Large-scale database migrations are also performed with it. - Source: / 8 months ago
  • Ingesting an S3 file into an RDS PostgreSQL table
    I'm using Redshift for a while now, and one feature I find particularly useful, is the ability to load a table from the content of an S3 file:. - Source: / 10 months ago
  • DeWitt Clause, or Can You Benchmark %DATABASE% and Get Away With It
    Amazon Web Services, including Athena, Aurora, and Redshift. You may perform benchmarks or comparative tests or evaluations (each, a “Benchmark”) of the Services. If you perform or disclose, or direct or permit any third party to perform or disclose, any Benchmark of any of the Services, you (i) will include in any disclosure, and will disclose to us, all information necessary to replicate such Benchmark, and (ii)... - Source: / 10 months ago
  • AWS Summit London 2022 day recap
    Amazon Redshift still remains a bit of a mystery to me, even after a whole session on it unpacking loads of its features, possibilities and use cases. Trying to draw some parallels in my head with BigQuery - Google Cloud Platform's own cloud data wharehouse service, which I know well - also didn't help much. So it remains one of those things that now I know a little bit more about than yesterday, but still feels... - Source: / 11 months ago
  • A modern data stack for startups
    With data warehouse solutions (BigQuery, Snowflake, Redshift) going mainstream, modern data stacks are becoming increasingly boring - great news if you're starting from scratch! - Source: / 11 months ago
  • The Difference Between Data Warehouses, Data Lakes, and Data Lakehouses.
    The video below gives an in-depth understanding of the lakehouse approach using Amazon Redshift. It uses AWS S3 to store data since Redshift is strictly a relational database. - Source: / 11 months ago
  • How hard is for DevOps to transfer from working on a private cloud to a public cloud
    Redshift is a service hosted and managed by AWS: Https:// - Source: Reddit / about 1 year ago
  • 10 AWS Services that use SQL
    Like Amazon Aurora, Amazon Redshift is used by large enterprises. However, Redshift is more complex, can handle more data, and is referred to as a data warehouse. This is because Redshift is built for OLAP (Online Analytical Processing). - Source: / about 1 year ago
  • Analytics Stacks for Startups
    The main DWH offerings that meet the above expectations are Snowflake, Google Bigquery, and Amazon Redshift. Featurewise, these three have similar functionalities but there are differences, e.g. How long it takes to spin up new compute resources or how much maintenance work they need. Costwise, it seems they end up with similar numbers on your bill, depending on which blog post you read. - Source: / about 1 year ago
  • Migrating to Snowflake, Redshift, or BigQuery? Use Datafold to Avoid these Common Pitfalls
    Although we’ve focused on Snowflake in this article, the same features of Datafold can be used for other cloud products like Redshift or BigQuery. - Source: / over 1 year ago
  • To what extent do you use SQL in your job?
    I'm not a business analyst but a software developer. I've worked quite a bit with event data. Think "Order Completed", "User Signed Up" and "Subscription Cancelled". When those events get channelled into a column-store database like Redshift or Clickhouse, you can answer a lot of advanced questions using SQL. In particular, Clickhouse has lots of useful functions for analysing datasets. See this analysis of GitHub... - Source: Reddit / over 1 year ago
  • Performance capabilities of data warehouses and how Cube can help
    Snowflake Data Cloud, Google BigQuery, and Amazon Redshift are all good examples of such data warehouses and the most used and popular choice for storing huge amounts of data. If your company has a data warehouse in use, chances are it's one of these behemoths. - Source: / over 1 year ago
  • Your Guide to Creating a Warehouse-First Data Analytics Stack
    Redshift is a data warehouse owned by Amazon Web Services (AWS). Redshift is a relational data warehouse and, therefore, accepts only structured data types. Redshift requires some sort of management in the sense that, in times of high demand, if you need to scale, then you need to handle that manually by adding new nodes. Usage costs a minimum of $0.25 based on the type and number of nodes in your cluster. In... - Source: / over 1 year ago
  • Start Building a Better CDP for Free With RudderStack Cloud Free
    RudderStack does not persist any of your customer data. RudderStack builds your CDP on your data warehouse, with support for cloud data warehouses like Amazon Redshift, Google BigQuery, and Snowflake. No more paying your CDP vendor a premium to store your data. No more concerns about whether your CDP vendor is keeping your customer data private and secure. No more crossing your fingers and hoping the BI, ML, or AI... - Source: / over 1 year ago
  • The Data Trinity
    The storage component is simply where the data lives after extraction and loading. The most common artifact is a data warehouse or data lake depending on conceptual design. The most common services in this category are AWS Redshift, Google cloud Big query and Snowflake. - Source: / over 1 year ago
  • Migrating to AWS
    Over time, we should have only dockers and lambda functions in our compute. While doing this, we should also discard the EC2 instances one by one and move onto Fargate. Drop the Kafka or other messaging services and move to Kinesis, EventBridge, SNS or SQS, as per the requirement. Migrate to cloud native databases like Aurora, DocumentDB, DynamoDB, and other purpose built databases like TimeStream, Keyspace,... - Source: / over 1 year ago

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