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What is Riak?

Riak is a NoSQL database from Basho Technologies in Bellevue, Washington.

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Recent Reviews

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Riak, a versatile database, has been widely utilized by various teams within organizations for a range of purposes. Users have found it …
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My Riak Review

9 out of 10
December 11, 2015
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 …
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What is Riak?

Riak is a NoSQL database from Basho Technologies in Bellevue, Washington.

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Riak Technical Details

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Reviews and Ratings


Community Insights

TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!

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.

Attribute Ratings


(1-6 of 6)
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Nicholas Adams | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
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.
  • 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
  • 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
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.
Adam Stern | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
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.
  • 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.
  • 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.
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.
Score 10 out of 10
Vetted Review
Verified User
It is being used as a backend for a web application used for storage of generated daily merchant statements.
  • Consistency model is highly distributed, so uptime of our documents is always available.
  • Simple to use RESTful interface, which was easy to access from our Java application.
  • Data model using catalogs and indexes was simple, making it easy to store and retrieve our statements.
  • It does not have any native startup scripts in Linux.
  • Since it's built on Erlang, its a bit difficult to administer.
Riak is well suited for storing documents using a RESTful URL, such as files in byte format. I would not recommend using it for structured data with many relations.
Jared Holmberg | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
I used Riak's ability to link objects in the database as a way to build up a hierarchical tree of documents representing student administrative and testing data as part of a project to integrate across dozens of systems in a large technology and education company. Riak was used as the basis for the data model used in the operational data store.
  • If you're considering a NoSQL solution, one of Riak's strengths is that it is built to scale with very low management overhead. Compare Riak to something like HBase (requires a full Hadoop cluster, along with YARN, and Zookeeper), and you'll find it's much easier to set up and maintain.
  • Schemaless design in Riak makes it really easy to apply whatever design you like. Since you're not locked into seeing things just the SQL way, you've got more freedom with the type of data you store and the way you store it.
  • Riak is highly reliable. It's built on a platform that's meant to be incredibly resistant to failure. If you run in Riak in a cluster or cloud based environment, you can trust that it will be very dependable.
  • At the time I was using Riak, data was stored as blobs so you couldn't query the data directly on the server. This has since been remedied with the addition of full-text search support.
When I'm considering doing analysis on a large data set using machine learning algorithms, admittedly, Riak is not my first choice. I'd probably look into the idea of using something like Spark to run a distributed algorithm on my data. That means I'd have to copy data out of Riak into HDFS to run it. If you had good integration with Spark, that would be a welcome addition. That would save a lot of time in moving data between the Riak cluster and the HDFS cluster.
December 11, 2015

My Riak Review

Jeff Peck | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
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.
  • 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.
  • 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.
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.
Gerald Chenvert | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
We use Riak as a datacenter/cloud replicating noSQL database. It is being used by various teams in our organization to write data which is then replicated to the cloud for cloud based service lookups. Riak allows us to provide data to the cloud in a secure manner via the "hub and spoke" replication model. Riak has proved instrumental in allowing us to move applications from a datacenter, to the cloud.
  • Riak is great at handling large volumes of requests. We've seen Riak perform well under large volume while keeping response times quite low.
  • Riak is also fast providing consistent sub 10ms reads in both the datacenter and cloud.
  • Flexible allowing storage of numerous data types. We heavily leverage this to store various JSON documents in a single bucket.
  • We really like the RESTful interface that is provided. Makes the learning curve almost invisible and provides a quick speed to market in using Riak.
  • 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.

Riak is well suited as a key value store. It does exactly what it says it does. If you have well known buckets/keys, Riak is a great solution for a ton of different use cases. The lack of ability to search is somewhat problematic for other use cases requiring this ability.

Also, while the ability to store a variable array of data into a single bucket/key is extremely useful, if you have a use case requiring parts of that value to be updated independently, Riak does not support transactions so you open yourself up to contention issues if the data is being updated regularly in small portions. One solution to this is to use multiple bucket/key parts to store the data, which will remove the contention issue, but then you have to increase your Riak footprint which results in more buckets and can sometimes make things more difficult than needed. This has been a nagging issue we've had to deal with on multiple occasions.

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