Amazon Athena vs. RavenDB

Best suited for analyzing huge amounts of data by just querying on Amazon Athena. Amazon Athena is also best to integrate with Amazon Quickight for visualization and reporting of data. Easy to work with CSV, JSON, and columnar data formats like Parquet, and ORC. Less appropriate to work with AVRO data format and also stored procedures are not supported in Amazon Athena. The size of a single row is also limited to 32 MB.

Incentivized

RavenDB is very well suited for NoSQL beginners to start easily setting up and using a NoSQL database. Also to set up a high performance and high availability cluster is possible without reading tons of documentation. Very straightforward assistant! The performance is really high.

• Load Balance traffic analysis
• Big data report generation
• Micro services pattern query analysis

Incentivized

• Document Database - no Object-Relational Impedance Mismatch
• ACID support that is optimized for performance
• Can be easily integrated into automated tests (unit tests)
• Easily configurable via C# code
• Comes directly with RavenStudio - no SSMS or SQL Developer required
• In general low footprint when it comes to memory and disk consumption
• Useful safety nets for new developers - e.g. by default an exception is thrown when you make too many requests within a session

• Every dialect of SQL has some missing functions. I wish there was automated GROUP BY options here.
• There are connection problems back to Power BI occasionally.
• If you don't watch certain queries, it's possible that it takes a long time to run and charges you a lot of money.

Incentivized

• Developing methods is challenging if developers are unfamiliar with the accurate simulation approach.
• It does not allow you to replicating, or authorized access without first acquiring a license.
• The lack of evidence of tracking records in the enterprise systems raises several concerns about RavenDB.

We've had an excellent experience using RavenDB. Internally we are testing the newer features in 5.0 such as time series, which will effect the con specified previously dependent on the real world performance. We foresee that BattleCrate will continue to use RavenDB as we grow.

Easy to use. Scalable. Gets the job of data warehousing setup done. Using the datalake on S3 has become super convenient.

Incentivized

Really good .NET client that is very easy to use. The management studio is excellent and puts anything that Microsoft or Oracle have to shame. Very quick to develop with once the complexity hurdle has been overcome. Initially using it can be a bit painful until you fully grasp the event sourced nature of the indexing.

Had a question that was answered in minutes. Never used a NoSQL approach before, but was able to be proficient in a matter of hours. Easy to read API Documentation. 5 out 5 support in book, I have never once ran into an issue that wasn't quickly solved by either their support team or myself doing a quick search online.

RavenFS changed along the way and made us change the codes.

Amazon Athena, a product from Amazon, competes with offerings from Google and Microsoft. Overall, I think your database choice depends on some of the other applications you are running at your company. For example, if you are using Microsoft Power BI for reporting needs, you might want to consider going the Azure route.

Incentivized

RavenDB is just smarter than the competitors. The mapping reduction sorting is head and shoulders above everything else I've used. Nothing really approaches comparable in terms of complexity. Because of the searching of predetermined categories, read efficiency is terrible. RavenDB is a storage system designed for the current websites and functional prototypes. It has an easy-to-use interface and enables quick replication and backup installation. Furthermore, technical assistance responds quickly and walks you through the implementation and deployment procedures.

• It's easy to store and query data on S3. Multiple teams can query the same data to generate their reports. It removes the need for a full-fledged data warehouse for a startup. Saves costs.
• Improved team efficiency on monitoring user activities by easy logging and reporting.
• As the dataset gets heavier on S3, one needs to understand partitioning and that leads to the requirement of expertise.

Incentivized

• RavenDB has saved my customers a lot of money with their cloud services' tiered model. The database is able to grow with the project/company and can start out small at a low cost.
• RavenDB is free for three nodes and three CPUs, which makes it great for development scenarios. You're able to start rapidly building applications without having to worry about licensing.
• Scaling out has allowed us to use three small cloud servers when starting out and get the performance and throughput of a single larger server.