Riak vs. Scylla

Riak is well suited to applications such as:

Transaction logging e.g. financial transactions and/or exchange rates.

Storing time series data, especially IoT.

Storing massive amounts of data e.g. corporation wide backups, data lakes etc.

A fully s3 compatible replacement for Amazon s3 ensuring data privacy.

Riak is not as well suited to:

Traditional RDBMS functions, especially those that join the outputs of one or more queries together to produce the desired result.

Scylla is well suited for high-throughput scenarios where keyed data must be read or written with consistently low latency. It's less appropriate for use cases requiring relational queries, secondary indexes, or more structured data sets.

• Highly available: If nodes go offline for any reason, the system still operates.
• Highly scalable: There is a minimum of 5 nodes, which can handle a lot by themselves. When scaling is required, it can be done easily, with minimal to no downtime on large scales.
• Very fast searching: Riak has SOLR indexing built-into the core product, which makes querying for data very fast.

Incentivized

• Low-latency reads
• CQL has a familiar syntax
• Parity with Cassandra
• Practical features

• Deletes!!! We've seen on numerous occasions where Riak has "resurrected" deleted data. We've worked with Basho numerous times and tried multiple changes to the way we interact with Riak to prevent the problem but it still remains. The deletes seem to reappear weeks, even months, after the delete was issued. We've had to work around this issue by providing a "deleted" flag for all data objects stored in Riak. Thus, we do no delete but simply flip the flag. Excess baggage we would really like to not have to worry about.
• Search. Currently there's no way to tell what data you have in Riak without already knowing a particular bucket/key. There is a way to list the keys for a given bucket but due to performance implications, this is not a viable method to lookup data. Especially when you have a large amount of keys in the bucket.

Incentivized

• Better documentation for best practices (e.g., how to effectively use connection pooling)

Right now, I'm on a project where we need databases that can run on embedded systems. Riak isn't necessarily the best fit for that scenario. But when we need a clustered database, that's where we'd start considering Riak.

Incentivized

Very easy-to-understand syntax--uses CQL (same as Cassandra), which has many similarities to standard SQL. There are some gotchas, however, that must be known during schema development.

Despite Basho going bankrupt and the project becoming fully open-source, community support is reasonably good, albeit a little slow at times. Paid enterprise-grade support is also available from former Basho engineers but the same company also contributes to the community support for free for basic questions or specific knowledge areas.

The Scylla cloud support team is incredibly responsive and proactive.

Because of the RESTful HTTP interface, the consistency model, and because of the catalog-driven data model, Riak was an easy win over Redis and Memcached.

Incentivized

Scylla has a quick learning curve (same as Cassandra) compared to other proprietary solutions like BigTable. It supports higher throughput and lower latency that other NoSQL databases like MongoDB, which sacrifice those features for more flexibility and unique features.

• Riak has been a key part of our company's build process for our client's search backend. It is valuable for is in that it provides a reliable way to view the current search index.

Incentivized

• Addresses latency requirements of our platform