About This Constellation ShortList™
Analytical relational database management systems (RDBMSs) have emerged as one of the most popular types of database services offered on public clouds. More popularly known as cloud data ware- house services, these offerings simplify the deployment and ongoing use of analytical database management systems on a small, moder- ate, or massive scale.
Any cloud service eliminates software and hardware deployment tasks and eases administrative burdens, but the standouts among cloud data warehouse services offer more automated capabilities. For example, they take advantage of cloud-native automation capa- bilities, such as serverless scaling and elastic compute and storage provisioning that goes up and down dynamically, based on usage. In addition, highly automated cloud data warehouse services add RDBMS-specific automation features that minimize, if not eliminate, previously manual administrative and workload-management tasks. Automated capabilities enable teams to focus on harnessing new data sources and supporting new workloads.
This ShortList presents Constellation’s pick of highly automated cloud data warehouse services. These services exploit the advan- tages of native-cloud automation features as well as “autonomous” self-tuning and self-optimization capabilities that can be achieved only when such services are run at scale in the cloud and can learn from outcomes with closed-loop, machine learning capabilities.
Constellation considers the following criteria for these solutions:
- Automated cloud data warehouse services enable customers to set up database instances through simple interfaces without having to make complex decisions or fixed commitments on storage or compute infrastructure.
- The service automatically scales by using serverless cloud compute capacity, sizing to initial requirements and scaling up and down as data stores and workloads change.
- Database management is also automated and responds to changes in scale and workloads, with no manual indexing or partitioning decisions to be made.
- The service is self-tuning, continuously learning from and optimizing the performance of workloads and queries rather than simply enforcing user- defined rules.
- Even automated products need some guidance from humans, so there should be provisions for setting workload priorities and service levels.
- Products should provide visibility into how automated performance-tuning decisions are made as well as ways to both boost performance and control costs.
- Since these are managed services, customers should not have to worry about software patches, upgrades, or backups.
The Constellation ShortList™
Constellation evaluates over 20 solutions categorized in this market. This Constellation ShortList is determined by client inquiries, partner conversations, customer references, vendor selection projects, market share and internal research.
- GOOGLE BIGQUERY
- ORACLE AUTONOMOUS DATA WAREHOUSE
Frequency of Evaluation
Each Constellation ShortList is updated at least once per year. Updates may occur after six months if deemed necessary.
Constellation clients can work with the analyst and the research team to conduct a more thorough discussion of this ShortList. Constellation can also provide guidance in vendor selection and contract negotiation.