Apache Cassandra vs. DBeaver

Apache Cassandra is a NoSQL database and well suited where you need highly available, linearly scalable, tunable consistency and high performance across varying workloads. It has worked well for our use cases, and I shared my experiences to use it effectively at the last Cassandra summit! http://bit.ly/1Ok56TK It is a NoSQL database, finally you can tune it to be strongly consistent and successfully use it as such. However those are not usual patterns, as you negotiate on latency. It works well if you require that. If your use case needs strongly consistent environments with semantics of a relational database or if the use case needs a data warehouse, or if you need NoSQL with ACID transactions, Apache Cassandra may not be the optimum choice.

Incentivized

If you are connecting to Snowflake and want to query from your laptop, I find that this is much easier to use than Snowflake's IDE. It allows us as a business intelligence team to more easily connect to our servers, and code with much less hassle. It would be less appropriate if you are only on an on-premises SQL server, in that case, I would just use SSMS.

Incentivized

• Continuous availability: as a fully distributed database (no master nodes), we can update nodes with rolling restarts and accommodate minor outages without impacting our customer services.
• Linear scalability: for every unit of compute that you add, you get an equivalent unit of capacity. The same application can scale from a single developer's laptop to a web-scale service with billions of rows in a table.
• Amazing performance: if you design your data model correctly, bearing in mind the queries you need to answer, you can get answers in milliseconds.
• Time-series data: Cassandra excels at recording, processing, and retrieving time-series data. It's a simple matter to version everything and simply record what happens, rather than going back and editing things. Then, you can compute things from the recorded history.

Incentivized

• Data import/export and SQL Script generation are quick and simple to do.
• Fairly intuitive when viewing/editing table data.
• Ability to save SQL scripts per server and recall them easily.
• Handy intelligence when writing queries, functions, and stored procs.

Incentivized

• Cassandra runs on the JVM and therefor may require a lot of GC tuning for read/write intensive applications.
• Requires manual periodic maintenance - for example it is recommended to run a cleanup on a regular basis.
• There are a lot of knobs and buttons to configure the system. For many cases the default configuration will be sufficient, but if its not - you will need significant ramp up on the inner workings of Cassandra in order to effectively tune it.

Incentivized

• Some icons are kinda small and difficult to understand what they do
• The spanish translation could be better
• I think there are many functions that could be useful for me but I don't know what they do

I would recommend Cassandra DB to those who know their use case very well, as well as know how they are going to store and retrieve data. If you need a guarantee in data storage and retrieval, and a DB that can be linearly grown by adding nodes across availability zones and regions, then this is the database you should choose.

Incentivized

It’s great tool but it can be complicated when it comes administration and maintenance.

Incentivized

Sometimes instead giving straight answer, we ‘re getting transfered to talk professional service.

Incentivized

Not a lot of users have DBeaver so fewer resources are available online to help you if you have any issues. When I was trying to figure out how to create my own ER diagrams, it was a little tough to find resources

Incentivized

We evaluated MongoDB also, but don't like the single point failure possibility. The HBase coupled us too tightly to the Hadoop world while we prefer more technical flexibility. Also HBase is designed for "cold"/old historical data lake use cases and is not typically used for web and mobile applications due to its performance concern. Cassandra, by contrast, offers the availability and performance necessary for developing highly available applications. Furthermore, the Hadoop technology stack is typically deployed in a single location, while in the big international enterprise context, we demand the feasibility for deployment across countries and continents, hence finally we are favor of Cassandra

Incentivized

MySQL workbench from MySQL only supports MySQL databases and it only provides basic functionality. On top of that, the user experience could be quite confusing for first-time users. SSMS from SQL server doesn't support inline editing nicely. The view for inline editing and view data is different, making it uncomfortable to use. All in all, DBeaver is the best tool when you manage a lot of databases with different types.

Incentivized

• I have no experience with this but from the blogs and news what I believe is that in businesses where there is high demand for scalability, Cassandra is a good choice to go for.
• Since it works on CQL, it is quite familiar with SQL in understanding therefore it does not prevent a new employee to start in learning and having the Cassandra experience at an industrial level.

Incentivized

• Positive Ability to manage DBeaver and query ad-hoc quickly
• By having the queries saved it has saved developer time and thereby increased the ROI on the investment on the tool
• This has made firefighting quicker and freed up resources for more development work.

Incentivized