Likelihood to Recommend Apache Flume is well suited when the use case is log data ingestion and aggregate only, for example for compliance of configuration management. It is not well suited where you need a general-purpose real-time data ingestion pipeline that can receive log data and other forms of data streams (eg IoT, messages).
Read full review If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
Read full review Pros Multiple sources of data (sources) and destinations (sinks) that allows you to move data form and to any relevant data storage It is very easy to setup and run Very open to personalization, you can create filters, enrichment, new sources and destinations Read full review Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet. Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management. Read full review Cons It is very specific for log data ingestion so it is pretty hard to use for anything else besides log data Data replication is not built in and needs to be added on top of Apache Flume (not a hard job to do though) Read full review An aggregate pipeline can be a bit overwhelming as a newcomer. There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close. Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty. Read full review Likelihood to Renew I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
Read full review Usability NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
Read full review Support Rating Apache Flume is open-source so support is limited. Never the less, it has great documentation and best practices documents from their end-users so it is not hard to use, setup and configure.
Read full review Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
Read full review Implementation Rating While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
Tom Maiaroto Sr. Platform Developer / UX Designer / Optimization Engineer
Read full review Alternatives Considered Apache Flume is a very good solution when your project is not very complex at transformation and enrichment, and good if you have an external management suite like Cloudera, Hortonworks, etc. But it is not a real EAI or ETL like AB Initio or Attunity so you need to know exactly what you want. On the other hand being an opensource project give Apache a lot of room to personalize thanks to its plug-able architecture and has a very nice performance having a very low CPU and Memory footprint, a single server can do the job on many occasions, as opposed to the multi-server architecture of paid products.
Read full review We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need
Cassandra .
Cassandra 's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation;
Cassandra provides native Hadoop support.
Read full review Return on Investment Flume has simplified a lot many of our ingest procedures, easier to deploy and integrate than a classical EAI, reducing the time to market But opposed to EAIs if the project starts to grow in complexity Apache Flume project may not be as suitable Read full review Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models) You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB Read full review ScreenShots