TrustRadius Insights for Riak are summaries of user sentiment data from TrustRadius reviews and, when necessary, third party data sources.
Business Problems Solved
Riak, a versatile database, has been widely utilized by various teams within organizations for a range of purposes. Users have found it extremely valuable in migrating applications from data centers to the cloud, thanks to its ability to write data that is replicated in the cloud for service lookups. Additionally, Riak's unique feature of linking objects in the database has proven instrumental in constructing hierarchical trees of documents that represent important student administrative and testing data. It serves as a foundation for the operational data store's data model and plays a pivotal role as the backend for the weekly build cycle, which processes massive amounts of data for millions of industrial parts every week. Users have also leveraged Riak's capability to simultaneously feed metadata about each item, which ensures a reliable picture of what the front-end should look like and aids in purging old data. Furthermore, Riak serves as the main database for various web applications such as storage of generated daily merchant statements and for products like the Dittach Platform, where it stores information on all objects and documents managed within the environment. One of the key factors behind choosing Riak is its high availability, scalability, and built-in Apache SOLR for fast searching and indexing, which further enhances its suitability across different use cases.
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Riak Reviews
3 Reviews
Small Businesses (1-50 employees)
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Used as a data store in multiple scenarios. Everything from individual pair values such as datetime against currency exchange value through to large scale storage for videos and images. This was implemented in multiple clusters and tried on hardware varying from Raspberry Pi through to full rack mount servers. We also contributed towards the open source codebase.
Pros
Key-Value storage along with CRDTs
Fault tolerance
100% uptime
Massively scalable
Consistent response speeds
Multi datacentre replication
Geographic replication/redundancy
Is free to use
Lots of client libraries
Cons
Missing a free text search function
More security work
Multi-tenant reporting
More types of index optimised for different structures
Automating repairs especially after unclean shutdowns
WebDAV/Samba shares for Riak CS
Implementing the SQL queries from Riak TS in Riak KV
Settable replication bandwidth caps
Safemode start up after failure
More client integrations
Likelihood to Recommend
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.
Riak is used as the main database/K-V Store for the company's product, the Dittach Platform. It is used to store information on all the objects/documents we manage in our environment. We selected Riak because it is highly available, highly scalable, and has Apache SOLR built into the data store for fast searching and indexing.
Pros
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.
Cons
When the index definition changes, reindexing takes an extremely long time.
Support (both paid and community based) is very very lacking.
It is expensive to run.
Likelihood to Recommend
Riak is very good if you need a resilient data store that can handle large amounts of documents very fast. If you have 1,000,000 documents and need to execute complex queries, it is great. Riak's SOLR engine is fast, however if you have extremely high amount of queries in a very limited time range, it can fail in a bad way.
We are using Riak as a backend to our weekly build cycle that processes data for millions of industrial parts each week. The system that we actually feed to is not always 100% reliable, but we simultaneous feed metadata about each item to Riak to keep as a reliable picture of what our front-end *should* look like. This is also useful for purging old data. We built this system several years ago and have been using it consistently and reliably.
Pros
Reliability -- we rarely have to do anything to maintain our Riak instance. It is just online and available for whatever we throw at it.
The Riak Python client is an excellent tool and handles parallel writes/reads very well
There is a large and very receptive community or Riak users and developers who seem to be able to help with most technical questions that have arisen.
Cons
It would be nice if there was a better way to configure Riak for multiple nodes with less manual configuration. Really, it's not a big deal, but I am being asked to write a "con" so this is what I thought of.
Likelihood to Recommend
Riak is ideal for any situation that requires a reliable backend datastore.
However, for relatively small key-value lookups, I would recommend an in-memory data-store such as Redis.
