Why we built CockroachDB on top of RocksDB
In September of 2020 we introduced our own homecooked replacement for RocksDB - a storage engine called Pebble. You can read about our reasons for the switch in this blog. We have tremendous respect and appreciation for RocksDB and continue to recommend it. … If, on a final exam at a database class, you asked students whether to build a database on a log-structured merge tree (LSM) or a BTree-base
ProfaneDB
Protobuf defines your schema You alredy defined your models in Protobuf. Why should you to do it again to store them in your database? Based on RocksDB ProfaneDB doesn't want to reinvent the wheel. It uses RocksDB for great performance, the simplest way possible. gRPC interface ProfaneDB is written in C++, but can be used from any language that supports gRPC. It just needs your schema, and there i
Sysbench, a large server and fast SSD vs MyRocks, InnoDB and TokuDB
Sysbench, a large server and fast SSD vs MyRocks, InnoDB and TokuDB I have new performance results to share starting with modern sysbench, a large server, fast SSD and a database that is larger than RAM. Competitive read performance with much better space and write efficiency is why I like MyRocks and this is an example of that. However, we have work to do on read efficiency that will be apparent
MariaDB Server 10.2 GA Release Overview
This blog post looks at the recent MariaDB Server 10.2 GA release. Congratulations to the MariaDB Foundation for releasing a generally available (GA) stable version of MariaDB Server 10.2! We’ll definitely spend the next few weeks talking about MariaDB Server 10.2, but here’s a quick overview in the meantime. Keep in mind that when thinking about compatibility, this is meant to be the equivalent o
Introducing Badger: A fast key-value store written purely in Go - Dgraph Blog
Introducing Badger: A fast key-value store written purely in Go We have built an efficient and persistent log structured merge (LSM) tree based key-value store, purely in Go language. It is based upon WiscKey paper included in USENIX FAST 2016. This design is highly SSD-optimized and separates keys from values to minimize I/O amplification; leveraging both the sequential and the random performance
MyRocks: A space- and write-optimized MySQL database
At Facebook we use MySQL to manage many petabytes of data, along with the InnoDB storage engine that serves social activities such as likes, comments, and shares. While InnoDB provides great performance and reliability for a variety of workloads, it has inefficiencies on space and write amplification when used with flash storage. A few years ago, we built RocksDB, an embeddable, persistent key-val
FastoNoSQL - cross-platform GUI Manager for Redis, Memcached, SSDB, LevelDB, RocksDB, LMDB, UpscaleDB, Unqlite, ForestDB and Pika databases.
What is FastoNoSQL? FastoNoSQL is the GUI platform for NoSQL databases. Currently we support next databases: Redis Memcached SSDB LevelDB RocksDB UnQLite LMDB ForestDB (Available in PRO version) Pika (Available in PRO version) Dynomite (Available in PRO version) KeyDB You can connect all these databases and use them in any way you need. Also FastoNoSQL is IDE tool for NoSQL which works on the most
Sherpa Scales New Heights
Overview Sherpa is Yahoo’s distributed NoSQL key-value store offered as a hosted service. It is the cornerstone of Yahoo properties and hosts over 2,000 tables, 1 trillion records, and serves over 1 million queries a second across a wide spectrum of applications. Though core features described in prior publications (see References section) have solidly served applications over the years, we have c
Tech Talk: RocksDB Slides by Dhruba Borthakur & Haobo Xu of Facebook
Tech Talk: RocksDB Slides by Dhruba Borthakur & Haobo Xu of Facebook This presentation describes the reasons why Facebook decided to build yet another key-value store, the vision and architecture of RocksDB and how it differs from other open source key-value stores. Dhruba describes some of the salient features in RocksDB that are needed for supporting embedded-storage deployments. He explains typ
The Hive « The History of RocksDB
The History of RocksDB by Dhruba Borthakur November 26, 2013 Glimpse of the Past It was mid 2011, I had been developing HDFS/HBase for five years and I was in love with the Hadoop ecosystem. Here is a system that can store and query hundreds of petabytes of data without blinking an eye. Hadoop has always focused on scalability first and Hadoop’s scalability was increasing by leaps and bounds. It
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MyRocks
https://rocksdb.org/blog/2015/rocksdb-2015-h2-roadmap/
yinqiwen/ardb · GitHub - A redis protocol compatible nosql, it support multiple storage engines as backend like Google's LevelDB, Facebook's RocksDB, OpenLDAP's LMDB.
War Story: Speeding up Block-based Table Lookup
https://rocksdb.org/blog/323/the-1st-rocksdb-local-meetup-held-on-march-27-2014/
Benchmark
Facebookが新しいNoSQLであるApolloを発表
Wingify Engineering -
https://www.influxdata.com/blog/2014/06/20/leveldb_vs_rocksdb_vs_hyperleveldb_vs_lmdb_performance.html