Apache Drill vs. IBM Cloud Databases

if you're doing joins from hBASE, hdfs, cassandra and redis, then this works. Using it as a be all end all does not suit it. This is not your straight forward magic software that works for all scenarios. One needs to determine the use case to see if Apache Drill fits the needs. 3/4 of the time, usually it does.

Incentivized

Less Appropriate Scenario: 1) Small Scale or Low Budget Projects 2) Organizations with limited expertise in cloud technologies may find the learning curve steep, especially if they are not familiar with the IBM Cloud platform 3) If database requirements are highly dynamic and change frequently, the comprehensive features and management provided by IBM Cloud Databases might be overkill. A more flexible, self-managed solution could be preferable for adapting to rapid changes.

Incentivized

• queries multiple data sources with ease.
• supports sql, so non technical users who know sql, can run query sets
• 3rd party tools, like tableau, zoom data and looker were able to connect with no issues

Incentivized

• The ease of setup was effortless. For anyone with development experience, a few simple questions such as name and login data will get you set up.
• The web application to manage cluster settings, billing settings and even introspect the data was simple and most importantly worked all the time. This can not always be said for web interfaces of other products.

Incentivized

• deployment. Not as easy
• configuration isn't as straight forward, especially with the documentation
• Garbage collection could be improved upon

Incentivized

• Better cost reports, before just increasing to another tier, thus increasing the price. This is critical for early stage startups, where budget is tight.
• Add more data center options. As a comparison, a similar service, Aiven.io has dozen more options than Compose (basically all big cloud providers). We moved from AWS to Digital Ocean, which made us stop using Compose, since Compose forces us to be either on IBM or AWS.

Incentivized

if Presto comes up with more support (ie hbase, s3), then its strongly possible that we'll move from apache drill to prestoDB. However, Apache drill needs more configuration ease, especially when it comes to garbage collection tuning. If apache drill could support also sparkSQL and Flume, then it does change drill into being something more valuable than prestoDB

Incentivized

IBM is our trusted partner which never failed to meet our expectations. Stability, efficiency, usability and security is a must have for our business which is fully provided by IBM Cloud Databases

Incentivized

IBM Cloud Databases' pricing structure is easy to understand, and if you choose the right product, you can operate your system at minimal cost. Although there is ample documentation available, there doesn't seem to be a user community running on it, so specific usage know-how and troubleshooting can sometimes take longer than expected.

Support is helpful enough, but we haven't always had questions answered in a satisfactory manner. At one time we realized that Compose had stopped taking database snapshots on its two-per-day schedule, and had in fact not taken one for many days. Support recognized the problem and it was fixed, but the lack of proactive checks and the inability to share exactly what happened has caused us to look elsewhere for production work loads

Incentivized

compared to presto, has more support than prestodb. Impala has limitations to what drill can support apache phoenix only supports for hbase. no support for cassandra. Apache drill was chosen, because of the multiple data stores that it supports htat the other 3 do not support. Presto does not support hbase as of yet. Impala does not support query to cassandra

Incentivized

The reason why I choose IBM Cloud Databases is that the IBM cloud toolset is already being used in other functions of the company and by using IBM Cloud Databases, the other cloud tools are better embedded and integrated. If the company is set to use amazon tools, I would go for rds.

Incentivized

• Configuration has taken some serious time out.
• Garbage collection tuning. is a constant hassle. time and effort applied to it, vs dedicating resources elsewhere.
• w/ sql support, reduces the need of devs to generate the resultset for analysts, when they can run queries themselves (if they know sql).

Incentivized

• Prove use cases prior to administering entire platform, obtain ROI faster
• Able to achieve the technological components of our advanced analytics team without full scale purchase of AI platform
• Developed several studies to prove out cloud Db value, speed to deploy

Incentivized