Aerospike vs. Google Cloud SQL

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

Although Google Cloud SQL has room for improvement by addressing a minor lack of features, its features and services keep it high among other SQL database products. It is very fast compared to others. Since it is cloud-based, maintenance is also easier. Integration capabilities are also more than expected.

Incentivized

• Low latency
• Stable
• Highly configurable
• increasing features

Incentivized

• It has a easily and user understandable interface which provides it every necessary feature to come up with.
• It's backend is very strong that can help us to run big quieres without any hesitation.
• It's integration with other tools are one of the powerful feature which makes it more suitable to use.

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

• Increasing support for more database engines may enable a wider range of application needs to be met.
• Implementing and updating cutting-edge security features on a constant basis.
• Streamlining and enhancing the tools for transferring data to Google Cloud SQL from on-premises databases or other cloud providers.

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

Everything is great about using Google Cloud SQL, but I only dock marks for requiring the Cloud Auth Proxy to connect locally without using allowed networks. I get that it's necessary since it's behind a VPC but it's just a bit clunky to use. That being said, I wouldn't really call that a big deciding factor for Google Cloud SQL's usability.

Incentivized

We used the community edition.

Incentivized

GCP support in general requires a support agreement. For small organizations like us, this is not affordable or reasonable. It would help if Google had a support mechanism for smaller organizations. It was a steep learning curve for us because this was our first entry into the cloud database world. Better documentation also would have helped.

Incentivized

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

Incentivized

In our experience, we were down for almost a day, because Database Engineers at Rackspace weren't able to understand or provide a solution, and when they did, they had to recreate the database from the scratch. On a server, this is time consuming. When we faced a similar scenario on Google Cloud SQL it was as easy as to recover from the last image through the console. We were back up in less than 30 minutes. Such a solution, saves you money by reducing churn and keeping the business operating.

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

• With managed database system, it has given us near 100% data availability
• It has also improved web layer experience with faster processing and authentication using database fields
• Google Cloud SQL also gels up well with Google Analytics and other analytics systems for us to join up different data points and process them for deeper dives and analysis

Incentivized