Aerospike vs. Google Cloud Spanner

We were developing an advertisement time auction application, where we had to store the client's personal details, advertisement-related details, location, and many other details. Moreover, we required a promotion, cookies, and a few more details from the front end. All this information is heavy in terms of size and cannot be lost if the server crash. So, we required an extremely fast disk database with high scalability and low throughput.

Incentivized

Google Cloud Spanner is suited for limitless horizontal scaling while maintaining strong consistency which needs to support ACID. NoSQL databases work in scaling but no ACID support. RDBMS support ACID, but horizontal scaling is not as great. The API it provides result in some limitations to related areas of the code, such as connection pools or database linking framework. So high # of connection pools can vary.

Incentivized

• Low latency
• Stable
• Highly configurable
• increasing features

Incentivized

• Super high availability
• Scales automatically
• High standard SLA

Incentivized

• Load balancing per network segments.
• Reduction in price.
• Cross datacenter replication usage isn't so straightforward. Sometimes cross dc replication can have issues of bad data..

Incentivized

• Support for Views
• Support for more databases (schemas).
• More index types that can be supported (Functional)
• Backups (ie table/data backup) if data is deleted or truncate by accident.

Incentivized

If money isn't an issue, and you're not on the cloud, then I'd go with Aerospike. If you're the cloud ie, aws or azure, then i'd stick with dynamoDB or Cosmos then. Aerospike is definitely not something you want to put into the cloud. It doesn't work well w/ cross regions. If cross DC, you'll have to write some stuff for data integrity checks.

Incentivized

Could be easier to use and install. Also developer experience needs some work

We used the community edition.

Incentivized

Aerospike is much more performant than MongoDB, however there is much greater community adoption and support for mongo

Incentivized

At that point, we were looking at something [that] can hold our relational database, [...] provide stable connection, and maintain high ACID transition. BigTable is for nonrelational database so it was out of our [sight] very quickly. BigQuery is a data warehouse that can hold huge amount of data but not ideal for transition. AWS RDS is [...] similar to Spanner but because most of our services are already on GCP, so we went with Spanner.

Incentivized

• Being able to power the same workload on a fraction of the servers has led to better ROI for my application.
• Less servers needed also meant less time to manage the cluster, leading to savings in engineering time

• Backups specifically if transactional data is deleted. Restoring made us lose time.
• Sharding on Horizontal level was quick and easy. Deployment and increasing nodes is easy
• Large dataset handling.
• ACID compliance

Incentivized