When comparing Amazon Aurora and CockroachDB within the AWS ecosystem, several key differences and features stand out, particularly regarding scalability, deployment flexibility, and data consistency levels.

### Scalability

- **Amazon Aurora** is designed with a focus on high performance and scalability for read workloads. It achieves this by allowing up to 15 low latency read replicas across three availability zones, with automatic storage scaling up to 128TB per database instance. However, Aurora uses a single master for writes, which can limit its scalability for heavy write workloads[1].

- **CockroachDB**, on the other hand, is built to scale both reads and writes due to its multi-active nature. Every node in a CockroachDB cluster can handle both read and write operations, allowing it to scale horizontally with ease. This makes CockroachDB particularly well-suited for applications that require high scalability for both read and write operations[1][3].

### Deployment Flexibility

- **Amazon Aurora** is an AWS-native service, meaning it can only be run within the AWS ecosystem. This tight integration with AWS services can be beneficial for users who are already heavily invested in AWS, as it allows for seamless integration with other AWS services[1].

- **CockroachDB** offers more flexibility in terms of deployment. It can be run on any cloud, including AWS, or even on-premises. This makes it a versatile option for businesses that operate in multi-cloud or hybrid cloud environments. CockroachDB's ability to run anywhere provides users with the freedom to deploy their database in a way that best suits their operational requirements and avoids vendor lock-in[1][3].

### Data Consistency

- **Amazon Aurora** provides high availability and durability by replicating data across three availability zones and automatically backing up data to Amazon S3. While Aurora offers MySQL and PostgreSQL compatibility, its approach to data consistency is tailored to the characteristics of these relational database models[1].

- **CockroachDB** uses serializable isolation levels, the highest level of data consistency, which guarantees data accuracy across distributed transactions. This feature is particularly important for applications where data accuracy and consistency are critical, such as financial services or any other sector where transaction integrity is paramount[1].

Citations:
[1] https://dantheengineer.com/cockroachdb-vs-aws-aurora/
[2] https://www.reddit.com/r/CockroachDB/comments/149dytj/is_cockroachdb_cheaper_than_aurora_serverless_or/
[3] https://www.cockroachlabs.com/compare/amazon-aurora-vs-cockroachdb/
[4] https://www.cockroachlabs.com/webinars/cockroachdb-vs-aurora/
[5] https://news.ycombinator.com/item?id=16869902
[6] https://www.youtube.com/watch?v=_zAYQWdDxQg
[7] https://db-engines.com/en/system/Amazon%2BAurora%3BCockroachDB
[8] https://www.linkedin.com/posts/cockroach-labs_cockroachdb-vs-amazon-aurora-comparing-activity-7153385983487479809-DabO

### Comparison table on SQL, resiliency and cost
Below is a comparison of Amazon Aurora and CockroachDB on AWS, focusing on their ANSI SQL support, High Availability (HA), resiliency, and cost of operation:

| Feature | Amazon Aurora | CockroachDB |
|------------------|-------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------|
| **ANSI SQL Support** | Offers high compatibility with MySQL and PostgreSQL, both of which are ANSI SQL standards. This ensures a broad support for SQL features and functions[1]. | CockroachDB is designed to be PostgreSQL compatible, offering a significant degree of ANSI SQL support. However, there may be some limitations due to its distributed nature[1][16]. |
| **High Availability (HA)** | Utilizes a distributed, fault-tolerant, self-healing storage system that auto-scales up to 64TB per database instance. Supports up to 15 low-latency read replicas across three Availability Zones (AZs) for high availability[2]. | Achieves HA by replicating data across multiple nodes in a cluster, supporting multi-active (read and write) nodes. This allows for horizontal scaling and resilience against node failures[2][3]. |
| **Resiliency** | Aurora is designed for 99.99% availability, replicating data across three AZs within a region. It offers continuous backup to Amazon S3 and point-in-time recovery[2]. | Built to survive disk, machine, rack, and datacenter failures with minimal latency disruption and no manual intervention. CockroachDB replicates data three times by default and is designed to handle regional outages[2][8]. |
| **Cost of Operation** | While offering high performance, Aurora can be expensive, especially for high throughput or large storage requirements. Costs include instance hours, storage consumption, and data transfer fees[2][4]. | CockroachDB can be more cost-effective, especially for variable workloads or applications with global distribution needs. It offers a serverless option that scales with usage, potentially reducing costs for low or variable traffic patterns[4][5]. |

This comparison highlights the key differences between Amazon Aurora and CockroachDB in terms of ANSI SQL support, high availability, resiliency, and cost of operation within the AWS ecosystem. While both databases offer robust features for modern applications, the choice between them may depend on specific project requirements, budget constraints, and the need for global distribution or scalability.

Citations:
[1] https://dantheengineer.com/cockroachdb-vs-aws-aurora/
[2] https://www.peerspot.com/products/comparisons/amazon-aurora_vs_cockroachdb
[3] https://www.youtube.com/watch?v=sf44RgL0DhA
[4] https://www.reddit.com/r/CockroachDB/comments/149dytj/is_cockroachdb_cheaper_than_aurora_serverless_or/
[5] https://www.cockroachlabs.com/compare/amazon-aurora-vs-cockroachdb/
[6] https://www.yugabyte.com/blog/yugabytedb-vs-cockroachdb-vs-aurora/
[7] https://news.ycombinator.com/item?id=16869902
[8] https://www.cockroachlabs.com/customers/telecom-provider/
[9] https://slashdot.org/software/comparison/Amazon-Aurora-vs-CockroachDB-vs-Yugabyte/
[10] https://www.linkedin.com/posts/cockroach-labs_cockroachdb-vs-amazon-aurora-comparing-activity-7153385983487479809-DabO
[11] https://db-engines.com/en/system/Amazon%2BAurora%3BCockroachDB
[12] https://db-engines.com/en/system/Amazon%2BAurora%3BAmazon%2BRedshift%3BCockroachDB
[13] https://www.g2.com/compare/amazon-aurora-vs-cockroachdb
[14] https://db-engines.com/en/system/Amazon%2BAurora%3BCockroachDB%3BLinter
[15] https://sourceforge.net/software/compare/Amazon-Aurora-vs-CockroachDB/
[16] https://db-engines.com/en/system/Amazon%2BAurora%3BCockroachDB%3BPostgreSQL

### CockroachDB representative customers
The representative customers of CockroachDB, as mentioned in the provided sources, include companies from various sectors such as Infrastructure as a Service (IaaS), e-commerce, and financial services. Here are some anonymized examples of customers that have partnered with Cockroach Labs:

1. **An IaaS Company**: This customer operates 20 CockroachDB clusters with around 100+ nodes each, with the largest cluster being 160 nodes. The storage density across these clusters ranges from 2.5 to 10 TB/node, paired with a minimum of 22 VCPUs/node. The total throughput is approximately 200 operations per second per VCPU, with a mix of 70% reads and 30% writes/deletes. Their largest table contains 80 billion records. They are currently on version 22.2 with plans to upgrade to version 23.1[5].

2. **An E-commerce Company**: This customer has 335 clusters, with their largest single-region cluster consisting of 96 m6i.12xlarge (48 VCPU) nodes. Their largest cluster by data volume is 280TB (650TB at peak), with 1,323,000 ranges and a 122TB table. They are also the largest user of CockroachDB's changefeeds, with approximately 900 deployed across multiple clusters[5].

3. **Another E-commerce Company**: This customer uses a 36 m6i.4xlarge (16 VCPU) node multi-region cluster across AWS regions in Europe. The cluster serves between 100k–300k queries per second (QPS)[5].

4. **A Financial Service Company**: This customer operates an 18 node, 3 region cluster in the USA with 2 nodes per Availability Zone (AZ), using M6in.8Xlarge instances with 500GB per node/9TB total storage, and 576 vCPU running version 22.2.5. Their workload is bursty, peaking at market open with 50k operation executions per second, which includes 2 - 7 read or write operations per transaction[5].

These examples illustrate the diverse range of customers and workloads that CockroachDB supports, from large-scale data storage and high-throughput operations to multi-region deployments for global applications.

### Conclusion

Both Amazon Aurora and CockroachDB offer compelling features for different use cases within the AWS ecosystem. Aurora shines with its high performance and scalability for read-heavy workloads, seamless integration with AWS services, and compatibility with MySQL and PostgreSQL. CockroachDB stands out for its ability to scale both reads and writes, deployment flexibility across any cloud or on-premises environment, and strong guarantees on data consistency with serializable isolation levels. The choice between Amazon Aurora and CockroachDB will depend on the specific requirements of the application, including scalability needs, deployment preferences, and data consistency requirements.

Citations:
[1] https://www.cockroachlabs.com/security/
[2] https://www.linkedin.com/company/cockroach-labs
[3] https://www.cockroachlabs.com/careers/open-positions/
[4] https://www.cockroachlabs.com/blog/2-dot-0-perf-strides/
[5] https://www.cockroachlabs.com/blog/how-we-stress-test-and-benchmark-cockroachdb-for-global-scale/
[6] https://www.cockroachlabs.com/docs/cockroachcloud/compliance
[7] https://www.delphix.com/blog/modern-database-meets-modern-devops-data-platform
[8] https://research.contrary.com/reports/cockroach-labs