Apache CouchDB is an HTTP + JSON document database with Map Reduce views and bi-directional replication. The Couch Replication Protocol is implemented in a variety of projects and products that span computing environments from globally distributed server-clusters, over mobile phones to web browsers.
N/A
SingleStore
Score 9.5 out of 10
N/A
SingleStore aims to deliver the world’s fastest distributed SQL database for data-intensive applications: SingleStoreDB, which combines transactional + analytical workloads in a single platform.
Great for REST API development, if you want a small, fast server that will send and receive JSON structures, CouchDB is hard to beat. Not great for enterprise-level relational database querying (no kidding). While by definition, document-oriented databases are not relational, porting or migrating from relational, and using CouchDB as a backend is probably not a wise move as it's reliable, but It may not always be highly available.
Our workload is 100% analytical. We also have to ingest a lot of data each month. SingleStore is a perfect match for our needs because it has fast pipelines for data ingestion and great performance, even in large and complex queries. We need fast response times for our user interface and great performance in our ETL processes, which are rather complicated. SingleStore handles all of this very well.
It can replicate and sync with web browsers via PouchDB. This lets you keep a synced copy of your database on the client-side, which offers much faster data access than continuous HTTP requests would allow, and enables offline usage.
Simple Map/Reduce support. The M/R system lets you process terabytes of documents in parallel, save the results, and only need to reprocess documents that have changed on subsequent updates. While not as powerful as Hadoop, it is an easy to use query system that's hard to screw up.
Sharding and Clustering support. As of CouchDB 2.0, it supports clustering and sharding of documents between instances without needing a load balancer to determine where requests should go.
Master to Master replication lets you clone, continuously backup, and listen for changes through the replication protocol, even over unreliable WAN links.
We wish the product had better support for High Availability of the aggregator. Currently the indexes generated by the two different aggregators are not in the same sequential space and so our apps have more burden to deal with HA.
More tools for debugging issues such as high memory usage would be good.
The price was the one that kept us away from purchasing for the first few years. Now we are able to afford due to a promotion that gives it at 25% of the list price. Not sure if we'll continue after the promotion offer expires in another 2 years.
Because our current solution S3 is working great and CouchDB was a nightmare. The worst is that at first, it seemed fine until we filled it with tons of data and then started to create views and actually delete.
Couchdb is very simple to use and the features are also reduced but well implemented. In order to use it the way its designed, the ui is adequate and easy. Of course, there are some other task that can't be performed through the admin ui but the minimalistic design allows you to use external libraries to develop custom scripts
[Until it is] supported on AWS ECS containers, I will reserve a higher rating for SingleStore. Right now it works well on EC2 and serves our current purpose, [but] would look forward to seeing SingleStore respond to our urge of feature in a shorter time period with high quality and security.
SingleSore can perform transactions and operational analytics together in order to utilize their data and transform their business. SingleStore delivers a database that performs both functions. Before using SingleStore, we had different systems for OLTP queries and for OLAP analyses, and a number of ETL packages to bring data from the OLTP system to Reporting database.
Very responsive to trouble tickets - Often, I think, the SingleStore's monitoring systems have already alerted the engineers by the time I get around to writing a ticket (about 10 - 20 mins after we see a problem). I feel like things are escalated nicely and SingleStore takes resolving trouble tickets seriously. Also SingleStore follows up after incidents to with a post mortem and actionable takaways to improve the product. Very satisfied here.
it support is minimal also hw requirements. Also for development, we can have databases replicated everywhere and the replication is automagical. once you set up the security and the rules for replication, you are ready to go. The absence of a model let you build your app the way you want it
We allowed 2-3 months for a thorough evaluation. We saw pretty quickly that we were likely to pick SingleStore, so we ported some of our stored procedures to SingleStore in order to take a deeper look. Two SingleStore people worked closely with us to ensure that we did not have any blocking problems. It all went remarkably smoothly.
Vertica, Snowflake, SQL Server, Azure Data Warehouse, PowerBI, Aerospike, etc. From what I've seen MemSQL is well worth the cost when latency and data freshness needs are high, i.e. you need a lot of queries to run with UI latency (the query itself takes less than a second or so), with very fresh streaming fact and dimensional data. It will be more expensive per "unit of performance" but if you need that performance then it'll get the job done.
On-prem Vertica (note, not Eon) provides more knobs for optimizing a particular data set and set of queries against it and performs as well or better in a single table, fact table queries. It will also scale to data size more cheaply due to its on-disk model. For large queries against large data sets where data freshness isn't as important (and latency either is or isn't), I'd take Vertica, although if you need to do a lot of joins that will struggle). However, as they still are exclusively columnar, dimension table updates, and recalls based on them, can only be tuned to happen so fast (we could do much better than 10 seconds with 10-100 updates per second for raw replication, and Vertica's joins are always slow so recalls were worse).
Snowflake suffers similarly to Vertica in the data freshness, replication, and re-calc area; SF also doesn't give as many knobs to turn as Vertica for data set optimization but seems to be better at joins. If you have a lot of queries to run against a lot of data and joins are limited, you need query latency low and consistent but you don't need a ton of freshness, I'd stick with Vertica. If joins matter more, or you can accept notably-but-not-terribly worse performance, then Snowflake is fine and cheaper from what we've seen. (Again, I can't speak to SF vs Vertica Eon).
SQL Server and ADW we couldn't get to perform as well as the other options, but I'll say we didn't try that hard on those.
Aerospike is amazing as a KV store; however for OLAP use cases where you want to balance performance against the flexibility of queries against general event (time series) data (i.e. be able to roll up to different grains) then KV becomes challenging.
PBI is great if you want an integrated BI tool, but if you want an OLAP solution to build against, with some particular scale or performance needs to be mentioned above, I'd go with one of these other solutions. It really can be great for letting non-tech folks build relatively small data sets and quick insights for customers (internal or external), great leverage in that case.
As the overall performance and functionality were expanded, we are able to deliver our data much faster than before, which increases the demand for data.
Metadata is available in the platform by default, like metadata on the pipelines. Also, the information schema has lots of metadata, making it easy to load our assets to the data catalog.
