We compared MongoDB and SingleStore based on our users' reviews across four parameters. After reading all of the collected data, you can find our conclusion below.
MongoDB stands out for its flexibility, scalability, powerful query language, replication capabilities, and integration potential. SingleStore is praised for its high performance, scalability, real-time analytics, ease of use, and integration capabilities. Users of both platforms mention the need for enhancements in areas such as query execution, scalability, documentation, and user interface.
Features: MongoDB's valuable features include flexibility for working with dynamic data, scalability for large amounts of data, powerful query language, and reliable replication. SingleStore focuses on high performance, scalability, real-time analytics, seamless integration, ease of use, and intuitive interface.
Pricing and ROI: The setup cost for MongoDB is user-friendly and seamless. SingleStore is also straightforward and hassle-free. MongoDB's licensing process is described as straightforward, and SingleStore's is transparent and fair. Both products offer flexible pricing options catering to different budgets and needs. Users reported positive outcomes and benefits from adopting MongoDB. SingleStore users praised its performance, scalability, ease of use, and integration capabilities.
Room for Improvement: MongoDB users have suggested improvements to the query language, error handling, documentation, and performance optimization. SingleStore users have focused on enhancements to performance, data replication, scalability, and ease of use.
Deployment and customer support: The initial setup of MongoDB is straightforward, especially for those with prior experience in databases. It can be deployed in a couple of hours or even less, either on-premises or on the cloud. Some mention that cluster deployment can be a bit more complex and may take a couple of days. The availability of community support and the ease of learning the initial setup process makes it accessible to users without prior experience with MongoDB or traditional SQL databases. The duration required for deployment of SingleStore can vary depending on the experience of the person performing it. Cloud installations are simple and can be done by anyone (even someone less technical) in a matter of hours by following the provided instructions. Bare-metal installations might take a day for a new technical person, however, an experienced one can do it in an hour. MongoDB's customer service is consistently praised for exceptional assistance, responsiveness, and expertise. Users highlight prompt issue resolution, knowledgeable support staff, and effective communication. SingleStore customers express satisfaction with prompt and helpful assistance, knowledgeable staff, and responsive services.
The summary above is based on two interviews we conducted with MongoDB and SingleStore users. To access the review's full transcripts, download our report.
"Scalability seems good. I've never been even close to finding the limits. I've run a couple of notes of redundancy but I've never had any problems with scalability."
"One of the biggest benefits is the speed and flexibility of the documents, especially when it comes to modifications."
"MongoDB is easy to use."
"The most valuable features of MongoDB are the variety of translations available and the ability to deploy it on the cloud is useful. The cloud users can access the data, work on the data, and if they want to import or manipulate some data they can."
"The aggregation framework is very powerful when elaborating on data."
"The clustering is very good. It allows us to have high availability."
"Sharding is an excellent feature of MongoDB."
"I find the integration with other tools very easy."
"The product's initial setup phase was pretty straightforward, with no complex processes."
"MemSQL supports the MySQL protocol, and many functions are similar, so the learning curve is very short."
"The most valuable feature is the ability to create pipelines, streamline and extract data from the pipelines."
"It's a distributed relational database, so it does not have a single server, it has multiple servers. Its architecture itself is fast because it has multiple nodes to distribute the workload and process large amounts of data."
"The ability to store data in memory is a standout feature, enhanced by robust failover mechanisms."
"The product can automatically reinstall and reconfigure in case of a shutdown."
"The paramount advantage is the exceptional speed."
"It would be good to have scalability for clusters. For example, if we have three clusters, we should be able to increase to five clusters if required. I am not sure if such a feature is currently there. I hope there is good documentation for this."
"I feel that most people don't know a lot about MongoDB, so maybe they could add some more documentation and tutorials."
"More stable indexes would be helpful in a future release. That's been an issue for some time. I don't know if it's been fixed now but we transitioned to it because we needed a search index to be able to search for things and if that goes or starts disappearing, we have to move away from that solution. I don't know if they fixed it, last time I had this issue was three years ago so they might have solved it."
"A normal Oracle or database tester will take some time to gear up to MongoDB because the way of writing queries is different in MongoDB. There should be some kind of midway where a person who is coming from an Oracle background can write a query and get a response by using something like a select * statement or other such things. There should be some way for MongoDB to interpret these commands rather than making a person learn MongoDB commands and writing them. I struggled while writing these MongoDB commands. I had not seen such queries before. It was pretty difficult to get them. This is one of the areas where it would help from the improvement standpoint."
"The solution could include more integrations with other platforms."
"I think that MongoDB's search engine should be improved."
"There are some problems with bugs appearing in sharding when the data is too high."
"You need integration with other tools to run the query in MongoDB."
"The product can be developed further to provide more appropriate output to users as it is one of the areas where there are shortcomings."
"For new customers, it's very tough to start. Their documentation isn't organized, and there's no online training available. SingleStore is working on it, but that's a major drawback."
"It is not the optimal choice for direct data collection through queries, and it's more suited for aggregation tasks."
"Poor key distribution can significantly impact performance, requiring a backward approach in design rather than adding tables incrementally."
"We don't get good discounts in Pakistan."
"There should be more pipelines available because I think that if MemSQL can connect to other services, that would be great."
"Having the ability to migrate servers using a single command would be extremely beneficial."
MongoDB is ranked 1st in NoSQL Databases with 68 reviews while SingleStore is ranked 6th in Database as a Service with 7 reviews. MongoDB is rated 8.2, while SingleStore is rated 8.8. The top reviewer of MongoDB writes "Lightweight with good flexibility and very fast performance for searching data". On the other hand, the top reviewer of SingleStore writes "A reasonably priced product that offers good speed and seamless support". MongoDB is most compared with InfluxDB, Couchbase, ScyllaDB, Oracle NoSQL and Cassandra, whereas SingleStore is most compared with SQL Server, MySQL, Teradata, Oracle Database and YugabyteDB.
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SQreamDB is a GPU DB. It is not suitable for real-time oltp of course.
Cassandra is best suited for OLTP database use cases, when you need a scalable database (instead of SQL server, Postgres)
SQream is a GPU database suited for OLAP purposes. It's the best suite for a very large data warehouse, very large queries needed mass parallel activity since GPU is great in massive parallel workload.
Also, SQream is quite cheap since we need only one server with a GPU card, the best GPU card the better since we will have more CPU activity. It's only for a very big data warehouse, not for small ones.
Your best DB for 40+ TB is Apache Spark, Drill and the Hadoop stack, in the cloud.
Use the public cloud provider's elastic store (S3, Azure BLOB, google drive) and then stand up Apache Spark on a cluster sized to run your queries within 20 minutes. Based on my experience (Azure BLOB store, Databricks, PySpark) you may need around 500 32GB nodes for reading 40 TB of data.
Costs can be contained by running your own clusters but Databricks manage clusters for you.
I would recommend optimizing your 40TB data store into the Databricks delta format after an initial parse.
Morten, the most popular comparisons of SQream can be found here: www.itcentralstation.com
The top ones include Cassandra, MemSQL, MongoDB, and Vertica.