Localytics vs. MongoDB

For the price and the features available, Localytics is one of the best options. It is more robust in areas that we don't need it to be and overall there could be simpler flows for sending push notifications or performing actions that you need to do every week. Also, the data it sends back on how push notifications perform is basically useless. There needs to be more explanation on the impact notifications have on users. The data would always say that notifications drove less engagement but we would see engagement go up every time we sent a notification.

Incentivized

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.

Incentivized

• Great web interface which provides a couple of levels of pivoting and filtering of data
• Straight-forward integration for simpler use cases
• Access to raw data through S3 for use in your own data pipeline

Incentivized

• 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.

Incentivized

• The biggest thing I would like to see with Localytics is the capability for more correlations. The limited amount of correlations available does restrict the type of analyses that could be done with the data.
• An easier interface to move data into Microsoft Excel would be very useful, rather than creating annoying workarounds.
• More/better automatically scheduled reporting, as well as an Excel plug-in to access the data rather than being restricted to the Localytics interface.

• 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.

Incentivized

There is a lot of competition. I would renew if there isn't anything more exceptional that would justify the re-coding and implementation load costs

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.

Incentivized

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.

Incentivized

It would take several weeks to hear back from the billing team. It took 3 months to resolve an invoice last year. Their technical support is very responsive. I would typically get a response in under 24 hrs.

Incentivized

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.

Incentivized

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.

Incentivized

We have not used other products but are going to start exploring making a switch to a new platform.

Incentivized

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.

• Was our first provider of user-level event data
• Allows for many users to easily answer their own questions before making requests of the data team
• Raw data dumps gave the data team the ability to provide more in-depth analyses.

Incentivized

• 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