Organizations today look to the cloud for their compute and data storage needs. Amazon AWS is by far the current market leader in both revenue and number of customers, and its service ecosystem is the most complete. Amazon’s popular Simple Storage Service (S3) is an object store, meaning that data is stored as objects, along with associated metadata and identifiers. This architecture is inexpensive, scalable, and allows massive amounts of unstructured data to be more readily accessible and more easily analyzed. S3 is also the name of the API for accessing the data programmatically.
S3 has quickly become the standard protocol for object storage but there are alternative APls from major cloud providers. Many third-party solutions are now compatible with more than just S3, offering additional options to users. API compatibility could remain an issue, though. Even if the customer has control of the entire stack, making changes to the application is not always economically or technically feasible. To simplify data access and the migration process, some service providers offer a “compatibility mode” that allows customers to use the S3 API or a subset of it, along with their native API. Note that Amazon Identity and Access Management (11AM) should always be taken into account when considering the compatibility requirements of most applications that use an S3 interface.
Object storage is excellent for many use cases and applications, both in the cloud and on premises, and is becoming a very popular target for backup, archiving, content management, file-based and cloud-native applications, big data lakes, HPC, and so on. Most applications that deal with unstructured data can take advantage of an object store easily, and this contributes to its appeal.
Amazon S3 is relatively inexpensive compared to other storage options available from Amazon AWS, but its performance is not always consistent. Moreover, the real cost of the service is not always immediately obvious and could become an issue for some customers. The S3 pricing model is quite complex and depends on several factors:
- Type of data protection
- Data locality
- Storage tier
- 10 operations
- Data transferred out of AWS (egress)
At the end of the day, it is not easy to estimate the cost and it can be difficult to predict how it will evolve over time. The egress costs of public cloud services are what worry CFOs and project managers the most, limiting flexibility in the execution of a multi-cloud strategy.
Although Amazon AWS has a very compelling solution ecosystem, there are alternative solution providers with innovative services for vertical markets and use cases that offer interesting alternatives.
Thanks to the success of Amazon AWS S3, many competitors have begun providing similar services while trying to differentiate themselves on price, performance, and functionality.
Market Categories and Deployment Types
For a better understanding of the market and vendor positioning (Table 1), we assess how well alternatives to S3 are positioned to serve specific market segments.
- Small-to-medium enterprise: In this category we evaluate solutions on their ability to meet the needs of small to medium-sized companies. We also look at departmental use cases in large enterprises, where ease of use and deployment are more important than extensive management capabilities. data mobility, and feature set
- Large enterprise: For this category, offerings are assessed on their ability to support large and business-critical projects. Optimal solutions will have a strong focus on flexibility, performance, data services, and features to improve security and data protection. Scalability is another big differentiator, as is the ability to deploy the same service in different environments.
- Specialized: We assess solutions designed for specif1c workloads and use cases, such as application development, big data analytics, 1oT, and more.