Adabas vs. Aerospike

It's well suited for applications running on z/OS I wouldn't consider it for applications on other operating systems

Incentivized

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

• It's efficient
• uses relativly few resources

Incentivized

• Low latency
• Stable
• Highly configurable
• increasing features

Incentivized

• Using newer features of z/OS
• pricing

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

Converting to another DBMS is a huge project.

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

Adabas uses resources better than DB2, but it doesn't use newer features of the hardware or operating system.

Incentivized

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

Incentivized

• Every time we want to upgrade our computer, the pricing for adabas is a big concern

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