Find out what your peers are saying about Snowflake Computing, Microsoft, Google and others in Cloud Data Warehouse.
| Product | Market Share (%) |
|---|---|
| Amazon Redshift | 7.5% |
| Snowflake | 17.7% |
| Dremio | 9.4% |
| Other | 65.4% |
| Product | Market Share (%) |
|---|---|
| IBM Db2 Warehouse on Cloud | 0.8% |
| Snowflake | 17.7% |
| Dremio | 9.4% |
| Other | 72.1% |
| Product | Market Share (%) |
|---|---|
| IBM Netezza Performance Server | 4.4% |
| Oracle Exadata | 14.1% |
| Teradata | 13.2% |
| Other | 68.3% |
| Company Size | Count |
|---|---|
| Small Business | 27 |
| Midsize Enterprise | 21 |
| Large Enterprise | 27 |
| Company Size | Count |
|---|---|
| Small Business | 4 |
| Large Enterprise | 3 |
| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 5 |
| Large Enterprise | 33 |
Amazon Redshift is a fully administered, petabyte-scale cloud-based data warehouse service. Users are able to begin with a minimal amount of gigabytes of data and can easily scale up to a petabyte or more as needed. This will enable them to utilize their own data to develop new intuitions on how to improve business processes and client relations.
Initially, users start to develop a data warehouse by initiating what is called an Amazon Redshift cluster or a set of nodes. Once the cluster has been provisioned, users can seamlessly upload data sets, and then begin to perform data analysis queries. Amazon Redshift delivers super-fast query performance, regardless of size, utilizing the exact SQL-based tools and BI applications that most users are already working with today.
The Amazon Redshift service performs all of the work of setting up, operating, and scaling a data warehouse. These tasks include provisioning capacity, monitoring and backing up the cluster, and applying patches and upgrades to the Amazon Redshift engine.
Amazon Redshift Functionalities
Amazon Redshift has many valuable key functionalities. Some of its most useful functionalities include:
Reviews from Real Users
“Redshift's versioning and data security are the two most critical features. When migrating into the cloud, it's vital to secure the data. The encryption and security are there.” - Kundan A., Senior Consultant at Dynamic Elements AS
“With the cloud version whenever you want to deploy, you can scale up, and down, and it has a data warehousing capability. Redshift has many features. They have enriched and elaborate documentation that is helpful.”- Aishwarya K., Solution Architect at Capgemini
IBM dashDB family offers private and public cloud database solutions for transactional and analytic workloads, with IBM fully managed or client managed options with a Common SQL engine across all deployment options.
IBM Netezza Performance Server offers high performance, scalability, and minimal maintenance. It seamlessly integrates SQL for efficient data processing, making it ideal for enterprise data warehousing needs.
IBM Netezza Performance Server is known for its outstanding data processing capabilities. Its integration of FPGA technology, compression techniques, and partitioning optimizes query execution and scalability. Users appreciate its appliance-like architecture for straightforward deployment, distributed querying, and high availability, significantly boosting operations and analytics capabilities. However, there are areas for improvement, particularly in handling high concurrency, real-time integration, and specific big data functionalities. Enhancements in database management tools, XML integration, and cloud options are commonly desired, along with better marketing and community engagement.
What are the key features of IBM Netezza Performance Server?Industries rely on IBM Netezza Performance Server for robust data warehousing solutions, particularly in sectors requiring intensive data analysis such as finance, retail, and telecommunications. Organizations use it to power business intelligence tools like Business Objects and MicroStrategy for customer analytics, establishing data marts and staging tables to efficiently manage and update enterprise data. With the capacity to handle large volumes of compressed and uncompressed data, it finds numerous applications in on-premises setups, powering data mining and reporting with high reliability and efficiency.
