Rockset, ClickHouse, Apache Druid, or Apache Pinot? Which is the best database for customer-facing analytics?

Ingestion in Rockset works just like the other mentioned tools as you can insert data from streams, lakes, or operational databases—both by batching or streaming. But the biggest benefit of Rockset is that it’s optimized for ingest latency. “This means it’s good for reliable freshness as the newly ingested data is immediately available for querying,” says Tom.

2

ClickHouse

‍ClickHouse is an open-source, column-oriented, distributed, and OLAP database that’s very easy to set up and maintain. “Because it’s columnar, it’s the best architectural approach for aggregations and for ‘sort by’ on more than one column. It also means that group by’s are very fast. It’s distributed, replication is asynchronous, and it’s OLAP—which means it’s meant for analytics,” says Tyler Hannan, Senior Director of Developer Advocacy at ClickHouse.

#Databases #Relational Databases #Data Warehousing 56 social mentions

3

Apache Druid

“When you're dealing with highly concurrent environments, you really need an architecture that’s designed for that CPU efficiency to get the most performance out of the smallest hardware footprint—which is another reason why folks like to use Apache Druid,” says David Wang, VP of Product and Corporate Marketing at Imply. (Imply offers Druid as a service.)

#Databases #Data Analysis #Relational Databases 10 social mentions

4

Apache Pinot

The biggest value behind Apache Pinot is that you can index each column, which allows it to process data at a super fast speed. “It’s like taking a pivot table and saving it to disk. So you can get this highly dimensional data with pre-computed aggregations and pull those out in what seems like supernaturally fast time,” says Tim Berglund, Developer Relations at StarTree. (StarTree.ai offers Pinot as a service.)

#Big Data #Data Dashboard #Databases