Pinot: Difference between revisions
Jump to navigation
Jump to search
No edit summary |
No edit summary |
||
| (One intermediate revision by the same user not shown) | |||
| Line 1: | Line 1: | ||
Pinot is a realtime distributed OLAP datastore, which is used at LinkedIn to deliver scalable real time analytics with low latency. It can ingest data from offline data sources (such as [[Hadoop]] and flat files) as well as online sources (such as [[Apache Kafka]]). Pinot is designed to scale horizontally. |
Pinot is a realtime distributed OLAP datastore, which is used at LinkedIn to deliver scalable real time analytics with low latency. It can ingest data from offline data sources (such as [[Hadoop]] and flat files) as well as online sources (such as [[Apache Kafka]]). Pinot is designed to scale horizontally. Pinot leverages [[Apache Helix]] for cluster management. |
||
https://github.com/linkedin/pinot |
Github: https://github.com/linkedin/pinot |
||
Architecture : https://github.com/linkedin/pinot/wiki/Architecture |
|||
http://engineering.linkedin.com/analytics/real-time-analytics-massive-scale-pinot |
|||
Latest revision as of 08:48, 13 June 2015
Pinot is a realtime distributed OLAP datastore, which is used at LinkedIn to deliver scalable real time analytics with low latency. It can ingest data from offline data sources (such as Hadoop and flat files) as well as online sources (such as Apache Kafka). Pinot is designed to scale horizontally. Pinot leverages Apache Helix for cluster management.
Github: https://github.com/linkedin/pinot
Architecture : https://github.com/linkedin/pinot/wiki/Architecture
http://engineering.linkedin.com/analytics/real-time-analytics-massive-scale-pinot