Apache Cassandra vs. InterSystems Caché (legacy product)

Cassandra excels in a broad range of applications -- especially if you understand its data model and write your applications accordingly. It's an excellent choice for time-series data, and a poor choice for application queues. It performs the best if you can simply record history and compute from it, rather than going back and editing or deleting things a lot.

Incentivized

Great for a one for all, heavy bundled, and licensed solution. When trying to evolve and scale, it can be very limiting. Think future proof as something that fits now could be hard to change later and work around.

Incentivized

• High Availability - we utilize the data replication features of Cassandra. This enables us to access our data even when several nodes have gone down
• Data Locality - our architecture combines Cassandra storage nodes and computation nodes in the same machine. This enables us to utilize data locality and limit expensive network IO to read data.
• Elasticity - Cassandra is a shared nothing architecture. Nodes can be added very easily and they discover the network topology. As soon as a node has joined the Cassandra ring, the data is redistributed among the existing nodes and streamed to it automatically.

Incentivized

• Fast development
• the language light to learn.
• Different ways to access data
• Good internal documentation, which is also available online.

Incentivized

• No Ad-Hoc Queries: Cassandra data storage layer is basically a key-value storage system. This means that you must "model" your data around the queries you want to surface, rather than around the structure of the data itself.
• There are no aggregations queries available in Cassandra.
• Not fit for transactional data.

Incentivized

• The great functionality hides behind an old UI that can be cumbersome to navigate, making Cache configurations take more time.
• The easy installs of Cache need specific setups to work well, and if yours is unique or if your servers are highly specialized on a networking level in terms of ports, VMs, or otherwise, then there may be some difficulties getting things to work.

Incentivized

I would recommend Cassandra DB to those who know their use case very well, as well as know how they are going to store and retrieve data. If you need a guarantee in data storage and retrieval, and a DB that can be linearly grown by adding nodes across availability zones and regions, then this is the database you should choose.

Incentivized

It’s great tool but it can be complicated when it comes administration and maintenance.

Incentivized

Sometimes instead giving straight answer, we ‘re getting transfered to talk professional service.

Incentivized

Apache Cassandra has the best of both worlds, it is a Java based NoSQL, linearly scalable, best in class
tunable performance across different workloads, fault tolerant, distributed, masterless, time series database. We have used both Apache HBase and MongoDB for some use cases which were within hadoop setup and JSON (JavaScript Object Notation) document store respectively, but given the overall factors favoring Apache Cassandra, it is a technology choice for multiple platforms!

Incentivized

I've only worked with products that do one thing before, but there's so much that Cache offers versus piecing different services together manually. Not only does the product offer a more robust tool-set, but the support is wonderful and I've never encountered a better vendor in any industry in terms of how well they interact with their customers and care about helping you solve your problems. They want you to grow and to get better.

Incentivized

• The open source version of Cassandra is only suggested for learning the basic concepts and play with its core features. Unless you really want to invest a lot in your developers and architects knowing every detail of Cassandra, I prefer the DataStax enterprise version. Although the license cost is relatively high, I think they it is worth it. I'm thinking about the support, the monitoring tool OpsCenter, and the integration of Solr and Spark (for data analysis).
• Cassandra didn't fully replace our old and traditional relation database Oracle. In addition, it opens another door for us to deal with some special business use cases that NoSQL database can do better in a more feasible and efficient way.

Incentivized

• A fast ROI due to its rapid programing language allowing the developers to write reliable code in a very short period of time.

Incentivized