We compared MongoDB and InfluxDB based on our user's reviews in several parameters.
MongoDB offers flexibility, scalability, and robust replication capabilities, while customer service and support are highly praised. InfluxDB excels in handling large volumes of data and real-time monitoring, with a focus on query performance and storage optimization. Both products receive positive feedback on pricing, setup costs, and ROI, with InfluxDB offering competitive pricing options and transparent licensing terms. The key differences lie in MongoDB's document-oriented data model and powerful query language, contrasted with InfluxDB's emphasis on time series data management and integration options.
Features: The valuable features of MongoDB include flexibility, scalability, efficient handling of large data, document-oriented data model, support for multiple data structures, powerful query language, and robust replication and high availability capabilities. In contrast, InfluxDB stands out for its ability to handle large volumes of data, real-time monitoring capabilities, ease of use and scalability. It offers efficient data storage and querying capabilities, supports different data types, continuous queries, and provides robust platform and integration options for time series data management.
Pricing and ROI: The setup cost for MongoDB has received feedback, while InfluxDB is praised for its reasonable setup costs and transparent pricing. Users have found the setup cost for InfluxDB to be straightforward, simplifying the overall process. InfluxDB's licensing terms are also appreciated for their flexibility and ease of use., MongoDB provided a positive ROI based on user feedback. InfluxDB had a highly positive ROI, praised for its fast data storage, scalability, and ease of use.
Room for Improvement: MongoDB users have highlighted areas for improvement, including performance optimization, data replication, query language flexibility, and user-friendly database management tools. InfluxDB users seek improvements in query performance, data storage optimization, documentation, scalability, and support services.
Deployment and customer support: Based on user feedback, MongoDB users mentioned varying durations for implementation, with some indicating separate timeframes for deployment and setup. InfluxDB users also mentioned separate timeframes, but it is important to consider the context of usage for accurate evaluation., MongoDB's customer service is highly valued for its timely assistance and knowledgeable responses, while InfluxDB's support is praised for its promptness and reliability. Both products have received positive reviews for their customer service.
The summary above is based on 34 interviews we conducted recently with MongoDB and InfluxDB users. To access the review's full transcripts, download our report.
"The most valuable features are aggregating the data and integration with Graphana for monitoring."
"InfluxDB's best feature is that it's a cloud offering. Other good features include its time-series DB, fast time-bulk queries, and window operations."
"The solution is very powerful."
"In our case, it started with a necessity to fill the gap that we had in monitoring. We had very reactive monitoring without trend analysis and without some advanced features. We were able to implement them by using a time series database. We are able to have all the data from applications, logs, and systems, and we can use a simple query language to correlate all the data and make things happen, especially with monitoring. We could more proactively monitor our systems and our players' trends."
"The user interface is well-designed and easy to use. It provides a clear overview of the data, making it simple to understand the information at hand."
"The most valuable feature of the solution is we can use InfluxDB to integrate with and plug into any other tools."
"InfluxDB is a database where you can insert data. However, it would be best if you had different components for alerting, data sending, and visualization. You need to install tools to collect data from servers. It must be installed on Windows or Linux servers. During installation, ensure that the configuration file is correct to prevent issues. Once data is collected, it can be sent to InfluxDB. For visualization, you can use open-source tools like Grafana."
"The most valuable features of InfluxDB are the documentation and performance, and the good plugins metrics in the ecosystem."
"I found that MongoDB is most valuable for storing school-related queries. It's also user-friendly, and I found no difficulty accessing it. Setting it up is easy too."
"The initial setup isn't really that complex."
"It is convenient to use because we can do manipulations with the JSON data that we get. There are also a lot of joins and associations with MongoDB, which makes it easy to use for us."
"One of the biggest benefits is the speed and flexibility of the documents, especially when it comes to modifications."
"The clustering is very good. It allows us to have high availability."
"MongoDB has a simple data-loading interface."
"The solution's most important aspect is its seamless database."
"It facilitates the generation of heatmaps for graphical data analysis."
"InfluxDB is generally stable, but we've encountered issues with the configuration file in our ticket stack. For instance, a mistake in one of the metrics out of a hundred KPIs can disrupt data collection for all KPIs. This happens because the agent stops working if there's an issue with any configuration part. To address this, it is essential to ensure that all configurations are part of the agent's EXE file when provided. This makes it easier to package the agent for server installation and ensures all KPIs are available from the server. Additionally, the agent cannot encrypt and decrypt passwords for authentication, which can be problematic when monitoring URLs or requiring authentication tokens. This requires additional scripting and can prolong service restart times."
"InfluxDB cannot be used for high-cardinality data. It's also difficult and time-consuming to write queries, and there are some issues with bulk API."
"The solution's UI can be more user-friendly."
"InfluxDB can improve by including new metrics on other technologies. They had some changes recently to pool data from endpoints but the functionality is not good enough in the industry."
"In terms of features that I would like to see or have, in the community version, some features are not available. I would like to have clustering and authentication in the community version."
"I've tried both on-premises and cloud-based deployments, and each has its limitations."
"The solution doesn't have much of a user interface."
"The error logging capability can be improved because the logs are not very informative."
"We'd like technical support to respond faster to queries."
"MongoDB should be more stable, and support should be more efficient."
"It could be much more flexible like SequoiaDB. I would like to see more flexibility in the next release, especially when working with Microsoft Windows. A lot of people struggle with MongoDB because of their Windows versions. But Linux is faultless and mostly runs nicely."
"It would help if MongoDB offered a light solution for small projects."
"It would be much more useful if I have an admin user and a password."
"Simplifying the aggregation framework would be an improvement."
"MongoDB should not be used for reporting, analytics, or number-crunching tasks."
"The solution could have more integration."
InfluxDB is ranked 3rd in NoSQL Databases with 8 reviews while MongoDB is ranked 1st in NoSQL Databases with 70 reviews. InfluxDB is rated 7.6, while MongoDB is rated 8.2. The top reviewer of InfluxDB writes "A powerful, lightweight time series database with a simple query language and easy setup". On the other hand, the top reviewer of MongoDB writes "Lightweight with good flexibility and very fast performance for searching data". InfluxDB is most compared with Cassandra, Netdata, ScyllaDB, Cloudera Distribution for Hadoop and Couchbase, whereas MongoDB is most compared with Couchbase, ScyllaDB, Cassandra, Oracle NoSQL and Oracle Berkeley DB. See our InfluxDB vs. MongoDB report.
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