Apache Druid vs. Google Cloud Bigtable

It is extremely well suited to rapid ingest of data from large data sources, due to the fact that you can restrict what is ingested by column/field, so that you only pull in the data you actually want or need.

As stated earlier, the open source version could use better cluster management tools, and troubleshooting tools for failing jobs/tasks.

It works great for any use case that requires high throughput for reads and writes, for key-value kinda data. This enables you to use it for usecases where you need to retain data for a long term or even short term but then use it in pipelines to enrich data, sync states between backend and frontend or to quickly lookup say a user.

Incentivized

• Rapid ingest
• Limiting ingest to only the relevant fields/columns
• Easy ingest spec creation

• Analytics: is at Google's heart. No on can beat Google in this space and BigTable is one of its implementation of this. The insights you gain from BigTable are simply usable in your day to day activities and can help you make real difference.
• Speed: Processing TBs and PBs of data under minutes needs real efficient platform which is capable of doing much more than just processing data. All this data cannot be processed by a single machine, but rather huge pairs of machines working in conjuction with each other. BigTable's implementation is one of the finest and allows you achieve great speeds!
• Interface: is great. Google has segregated required task under logically placed buttons which takes no time by users to understand and get habituated.

Incentivized

• Security configuration is problematic
• Cluster management could have more features
• Troubleshooting incomplete tasks/jobs is a chore

• Global replication
• Complete SQL support
• Size limit of 1MB

Incentivized

For big IT firms like us, data is very important and it only holds its value if it can make sense to us. Therefore, Bigtable's usability is priceless when it comes to decision making based on data.

Incentivized

Google provides premium support services for BigTable which is absolutely blazing fast similar to Bigtable's performance.

Incentivized

As a hosted solution, that can be managed easily from the Google cloud platform, it enables the teams to think about business use cases vs thinking about the management of the database itself. It is easily to scale it up when you need more throughput or storage. This keeps the developers and the product folks happy.

Incentivized

• Integration with S3 storage has saved about 35% on our storage, over HDFS
• The rapid ingest has saved user's time in the query aspects of their applications.
• The ability to ingest from a variety of data sources has made overall user application queries much simpler

• Building new features that can leverage storage on the edge
• Realtime decision making
• Data enrichment

Incentivized