We compared MongoDB and Vertica based on our user's reviews in 4 parameters. After reading all of the collected data, you can find our conclusion below.
MongoDB is praised for its flexibility, scalability, advanced query language, and reliable customer service. Users suggest improving the query language, documentation, and performance optimization. MongoDB offers flexible pricing and provides a strong return on investment. Vertica highlights exceptional performance, scalability, ease of use, and advanced analytics capabilities. Users suggest improving the user interface, documentation, compatibility, and performance. Vertica offers reasonable pricing and receives positive ROI feedback.
Features: MongoDB's valuable features include flexibility in working with dynamic data structures, scalability for efficient data management, a powerful query language, and reliable replication. Vertica stands out for exceptional performance, ease of use, advanced analytics capabilities, and seamless integration with various data sources and tools.
Pricing and ROI: MongoDB offers a user-friendly and seamless setup cost, with flexible pricing options to cater to different budgets and needs. Vertica stands out with its relatively low setup cost compared to similar products, and its licensing is praised for its flexibility in customization. MongoDB's ROI is praised for its positive outcomes and benefits according to user feedback, while Vertica's ROI is highlighted in user reviews.
Room for Improvement: MongoDB users have emphasized the need for a more intuitive query language, improved error handling, better documentation, and faster query execution. Enhanced integration capabilities with popular programming languages and third-party tools are recommended. Vertica users have suggested improvements in the user interface, better documentation, increased compatibility and integration with other data management systems, and optimized performance and speed.
Deployment and customer support: MongoDB's customer support receives positive feedback and offers responsive and helpful technical teams, although limited to the enterprise version. Support is highly rated during data validation and migration events. Open-source users rely on community support. The initial setup for MongoDB varies. Some find it easy, especially on-premises or in private clouds, while others note complexity, particularly in feature-rich or clustered deployments. Vertica's customer support is praised for its knowledge and responsiveness, although some users report challenges with issue escalation and lengthy fixes. Users find Vertica's initial setup and deployment straightforward, typically taking a few days. Internal teams manage deployment easily with assistance from Vertica and vendor support.
The summary above is based on 150 interviews we conducted recently with MongoDB and Vertica users. To access the review's full transcripts, download our report.
"MongoDB is fast and efficient."
"MongoDB is flexible and it allows other applications to be added."
"It has visible benefits, actually, in terms of price of ownership if you compare it to, for example, Oracle."
"One of the first things I noticed when I had my first experience with MongoDB was how easy it was to use. I was expecting more difficulties or at least some challenges, but it was very, very easy to use. It's great technology, performs well, and is very convenient."
"We've found the product to be scalable."
"MongoDB is scalable and stable. The initial setup is very easy, and deployment and maintenance can be done by one person."
"We haven't had any issues with stability."
"The most valuable feature of MongoDB is the NoSQL database. In a SQL database, we need to join data together with a unique ID amongst other things, but in MongoDB, it's not required. We can directly receive all the information. The performance is very good. Additionally, they have frequent updates."
"Integrated R and geospatial functions are helping us improve efficiency and explore new revenue streams. "
"We are also opening new areas of business and potential new revenue streams using Vertica's analytic functions, most notably geospatial, where we are able to run billions of comparisons of lat/long point locations against polygon and point/radius locations in seconds. "
"Vertica enabled us to close large deals. Customers with large data sets had to be migrated from PostgreSQL to Vertica due to performance."
"The extensibility and efficiency provided by their C++ SDK."
"The fast columnar store database structure allows our query times to be at least 10x faster than on any other database."
"Eighty percent of the ETL operations have improved since implementing this solution."
"It has improved my organization's functionality and performance."
"Vertica's most outstanding features are the compression rates achieved and the speed of access of high volume data."
"It has certain limitations when it comes to handling hierarchical data, enforcing relationships, and performing complex joins, which should be taken into account when designing databases for applications with intricate data requirements."
"MongoDB would be improved with more integration, particularly for cloud environments like Google BigQuery."
"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."
"Lacks sufficient scalability and elasticity."
"The performance of the solution could be improved."
"The solution could include more integrations with other platforms."
"I think it would be good to have more search options such as an index resource. This will provide more options and resources to do advance searches."
"Its security features can be better. Sometimes, my higher authority says that we are not going to use MongoDB because it doesn't provide that much security for the RDBMS or relational data that we use for transactions. Instead of MongoDB, we will use Oracle Database because for a transactional service, you have to rely on RDBMS ACID properties. I would love to work on MongoDB by using my mobile phone. When I am working remotely or traveling and have some instances deployed on my server, I should be able to check through my mobile whether all the data is being pulled. GitHub has a similar feature, where it lets you read from the laptop, and you can also pull and push with your mobile phone. I would request MongoDB to provide such a feature. Basically, I want a mobile version for both iOS and Android versions."
"If you do not utilize the tuning tools like projections, encoding, partitions, and statistics, then performance and scalability will suffer."
"In my opinion, Vertica's documentation could be improved. Currently, there is not enough documentation available to gain a comprehensive understanding of the platform."
"It would be great if this were a managed service in AWS."
"I have found that coding support could be simplified."
"I would personally like to see extended developer tooling suited to Vertica – think published PowerDesigner SQL dialect support."
"It should provide a GUI interface for data management and tuning."
"Fact-to-fact joins on multi-billion record tables perform poorly."
"They could improve on customer service."
MongoDB is ranked 1st in NoSQL Databases with 70 reviews while Vertica is ranked 4th in Data Warehouse with 83 reviews. MongoDB is rated 8.2, while Vertica is rated 8.2. 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 Vertica writes " A user-friendly tool that needs to improve its documentation part". MongoDB is most compared with InfluxDB, Couchbase, ScyllaDB, Cassandra and Neo4j Graph Database, whereas Vertica is most compared with Snowflake, SQL Server, Amazon Redshift, Teradata and Microsoft Azure Synapse Analytics. See our MongoDB vs. Vertica report.
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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.