Revision ec2f64794bc8430c4f6b771f16136d7a0afe2c15 authored by Andrew Kryczka on 15 November 2016, 04:20:14 UTC, committed by Facebook Github Bot on 15 November 2016, 04:24:21 UTC
Summary: Adjusted AddToBuilder() to take lower_bound and upper_bound, which serve two purposes: (1) only range deletions overlapping with the interval [lower_bound, upper_bound) will be added to the output file, and (2) the output file's boundaries will not be extended before lower_bound or after upper_bound. Our computation of lower_bound/upper_bound consider both subcompaction boundaries and previous/next files within the subcompaction. Test cases are here (level subcompactions: https://gist.github.com/ajkr/63c7eae3e9667c5ebdc0a7efb74ac332, and universal subcompactions: https://gist.github.com/ajkr/5a62af77c4ebe4052a1955c496d51fdb) but can't be included in this diff as they depend on committing the API first. They fail before this change and pass after. Closes https://github.com/facebook/rocksdb/pull/1501 Reviewed By: yhchiang Differential Revision: D4171685 Pulled By: ajkr fbshipit-source-id: ee99db8
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USERS.md
This document lists users of RocksDB and their use cases. If you are using RocksDB, please open a pull request and add yourself to the list.
## Facebook
At Facebook, we use RocksDB as storage engines in multiple data management services and a backend for many different stateful services, including:
1. MyRocks -- https://github.com/MySQLOnRocksDB/mysql-5.6
2. MongoRocks -- https://github.com/mongodb-partners/mongo-rocks
3. ZippyDB -- Facebook's distributed key-value store with Paxos-style replication, built on top of RocksDB.[*] https://www.youtube.com/watch?v=DfiN7pG0D0khtt
4. Laser -- Laser is a high query throughput, low (millisecond) latency, key-value storage service built on top of RocksDB.[*]
4. Dragan -- a distributed graph query engine. https://code.facebook.com/posts/1737605303120405/dragon-a-distributed-graph-query-engine/
5. Stylus -- a low-level stream processing framework writtenin C++.[*]
[*] https://research.facebook.com/publications/realtime-data-processing-at-facebook/
## LinkedIn
Two different use cases at Linkedin are using RocksDB as a storage engine:
1. LinkedIn's follow feed for storing user's activities. Check out the blog post: https://engineering.linkedin.com/blog/2016/03/followfeed--linkedin-s-feed-made-faster-and-smarter
2. Apache Samza, open source framework for stream processing
Learn more about those use cases in a Tech Talk by Ankit Gupta and Naveen Somasundaram: http://www.youtube.com/watch?v=plqVp_OnSzg
## Yahoo
Yahoo is using RocksDB as a storage engine for their biggest distributed data store Sherpa. Learn more about it here: http://yahooeng.tumblr.com/post/120730204806/sherpa-scales-new-heights
## CockroachDB
CockroachDB is an open-source geo-replicated transactional database (still in development). They are using RocksDB as their storage engine. Check out their github: https://github.com/cockroachdb/cockroach
## DNANexus
DNANexus is using RocksDB to speed up processing of genomics data.
You can learn more from this great blog post by Mike Lin: http://devblog.dnanexus.com/faster-bam-sorting-with-samtools-and-rocksdb/
## Iron.io
Iron.io is using RocksDB as a storage engine for their distributed queueing system.
Learn more from Tech Talk by Reed Allman: http://www.youtube.com/watch?v=HTjt6oj-RL4
## Tango Me
Tango is using RocksDB as a graph storage to store all users' connection data and other social activity data.
## Turn
Turn is using RocksDB as a storage layer for their key/value store, serving at peak 2.4MM QPS out of different datacenters.
Check out our RocksDB Protobuf merge operator at: https://github.com/vladb38/rocksdb_protobuf
## Santanader UK/Cloudera Profession Services
Check out their blog post: http://blog.cloudera.com/blog/2015/08/inside-santanders-near-real-time-data-ingest-architecture/
## Airbnb
Airbnb is using RocksDB as a storage engine for their personalized search service. You can learn more about it here: https://www.youtube.com/watch?v=ASQ6XMtogMs
## Pinterest
Pinterest's Object Retrieval System uses RocksDB for storage: https://www.youtube.com/watch?v=MtFEVEs_2Vo
## Smyte
[Smyte](https://www.smyte.com/) uses RocksDB as the storage layer for their core key-value storage, high-performance counters and time-windowed HyperLogLog services.
## Rakuten Marketing
[Rakuten Marketing](https://marketing.rakuten.com/) uses RocksDB as the disk cache layer for the real-time bidding service in their Performance DSP.
## VWO, Wingify
[VWO's](https://vwo.com/) Smart Code checker and URL helper uses RocksDB to store all the URLs where VWO's Smart Code is installed.
## quasardb
[quasardb](https://www.quasardb.net) is a high-performance, distributed, transactional key-value database that integrates well with in-memory analytics engines such as Apache Spark.
quasardb uses a heavily tuned RocksDB as its persistence layer.
## Netflix
[Netflix](http://techblog.netflix.com/2016/05/application-data-caching-using-ssds.html) uses RocksDB on spinning disks to cache application data.
## TiKV
[TiKV](https://github.com/pingcap/tikv) is a GEO-replicated, high-performance, distributed, transactional key-value database. TiKV is powered by Rust and Raft. TiKV uses RocksDB as its persistence layer.
## Apache Flink
[Apache Flink](https://flink.apache.org/news/2016/03/08/release-1.0.0.html) uses RocksDB to store state locally on a machine.
## Dgraph
[Dgraph](https://github.com/dgraph-io/dgraph) is an open-source, scalable, distributed, low latency, high throughput Graph database .They use RocksDB to store state locally on a machine.
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