cockroach/docs/design.md at master · cockroachdb/cockroach
CockroachDB is a distributed SQL database. The primary design goals are scalability, strong consistency and survivability (hence the name). CockroachDB aims to tolerate disk, machine, rack, and even datacenter failures with minimal latency disruption and no manual intervention. CockroachDB nodes are symmetric; a design goal is homogeneous deployment (one binary) with minimal configuration and no r
Sorting in Cassandra
The Cassandra distributed data store is, at heart, a key/value storage system. Unlike pure key/value storage systems, however, Cassandra implements first-class notions of key and column ordering. Dominic Williams covered a good chunk of the topic wonderfully in his post “Cassandra: RandomPartitioner vs OrderPreservingPartitionerâ€. But his framing of the question is a bit different than mine and wa
What is Apache Cassandra? | Open Source Database | DataStax
Cassandra 4.1 is here! Learn more about the most contributor-friendly, easiest-to-run open-source Cassandra to date. Learn More Want to run open-source Cassandra with peace of mind? Learn about DataStax Luna, enterprise support for Apache Cassandra. Learn More Apache Cassandra is a distributed NoSQL database created at Facebook and later released as an open-source project in July 2008. Cassandra d
SSTable
SSTable is an abbreviation for Sorted String Table. It is the fundamental storage building block in few of the modern Log Structured Merge Tree(LSM) based distributed database systems and key-value stores. It is used in Cassandra, BigTable and other systems. SSTable stands for Sorted Strings Table which stores a set of immutable row fragments or partitions in sorted order based on row/partition ke
Using Merkle trees to detect inconsistencies in data
Cassandra's AntiEntropy service uses Merkle trees to detect the inconsistencies in data between replicas. Merkle tree is a hash tree where leaves contain hashes of individual data blocks and parent nodes contain hashes of their respective children. It provides an efficient way to find differences in data blocks stored on replicas and reduces the amount of data transferred to compare the data block
Whats the difference between Paxos and W+R>=N in Cassandra?
Yes, Paxos provides guarantees that are not provided by the Dynamo-like systems and their read-write quorums. The difference is how failures are handled and what happens during a write. After a successful write, both kind of systems behave similarly. The data will be saved and available for reading afterwards (until overwritten or deleted) and so on. The difference appears during a write and after
Cassandra 2.0 ã« CAS ãŒå…¥ã‚‹ã¨ã‹å…¥ã‚‰ãªã„ã¨ã‹ - kuenishi's blog
CASSANDRA-5062ã§CAS (Compare and Swap) を入れよã†ã¨ã„ã†è©±ã«ãªã£ã¦ã„るらã—ãã€ä¸€ä½“ã©ã‚“ãªã™ã”ã„アトミックブãƒãƒ¼ãƒ‰ã‚ャストを使ã†ã®ã‹æ°—ã«ãªã£ã¦ã„ãŸã€‚ã©ã†ã„ã†ã“ã¨ãªã®ã ã‚ã†ã¨ã‚¹ãƒ¬ãƒƒãƒ‰ã‚’ナナメèªã¿ã—ã¦ã¿ãŸã®ã ãŒâ€¦è°è«–ã®æµã‚Œã¨ã—ã¦ã¯ カウンターã ã‘ã˜ã‚ƒãªãã¦CASã»ã—ã„よãAPIã¨ã—㦠ZooKeeperã®ãƒãƒƒã‚¯ä½¿ã†ã®ãŒã‚·ãƒ³ãƒ—ルã§ã„ã‚“ã˜ã‚ƒã？ ã„ã‚„ã„やサーãƒãƒ¼ã®ç¨®é¡žå¢—ã‚„ã™ã¨ã‹ã‚ã‚Šå¾—ãªã„㗠基本方é‡ã¯ã€ã‚³ãƒ¼ãƒ‡ã‚£ãƒãƒ¼ã‚¿ãƒ¼ã¿ãŸã„ãªã®ã‚’レプリカセット毎ã«æ±ºã‚ã¦ãã“ã‹ã‚‰ Chain Replication ã½ã コーディãƒãƒ¼ã‚¿ãƒ¼ã©ã†ã‚„ã£ã¦æ±ºã‚ã‚‹ ã‚„ã£ã±Paxosã˜ã‚ƒã？ å†å®Ÿè£…ヤダよZAB使ãŠã†ã‚ˆZKã®å®Ÿè£…ã‚るよ （ãªã‚“ã‹ãƒ—ãƒãƒˆã‚³ãƒ«ä¸Šã®ç†ç”±ãŒã‚ã£ã¦ï¼‰ã‚„ã£ã±Paxos実装ã™ã‚‹ã—ã‹ãªã„ã‹â€¦ ã¨ãªã£ã¦ã€çµå±€ Jonathan Ellis ㌠Paxos ã‚’ç´ ã§å®Ÿè£…ã—ã¦ã—ã¾ã£ãŸæ¨¡
Why Cassandra Doesn’t Need Vector Clocks | Datastax
One of the notable features of Amazon's 2007 Dynamo paper was the use of vector clocks for conflict resolution. However, the two most prominent systems designed by engineers who worked on Dynamo -- Cassandra and DynamoDB -- both avoid the use of vector clocks in favor of finer-grained updates. To understand why, let's first look at the problem that vector clocks solve. Resolving conflicts with vec
Lightweight transactions in Cassandra 2.0 | Datastax
Background When discussing the tradeoffs between availability and consistency, we say that a distributed system exhibits strong consistency when a reader will always see the most recently written value. It is easy to see how we can achieve strong consistency in a master-based system, where reads and writes are routed to a single master. However, this also has the unfortunate implication that the s
Transactions - MongoDB Manual v8.0
In MongoDB, an operation on a single document is atomic. Because you can use embedded documents and arrays to capture relationships between data in a single document structure instead of normalizing across multiple documents and collections, this single-document atomicity obviates the need for distributed transactions for many practical use cases. For situations that require atomicity of reads and
Cassandra File System Design | Datastax
The Cassandra File System (CFS) is an HDFS compatible filesystem built to replace the traditional Hadoop NameNode, Secondary NameNode and DataNode daemons. It is the foundation of our Hadoop support in DataStax Enterprise. The main design goals for the Cassandra File System were to first, simplify the operational overhead of Hadoop by removing the single points of failure in the Hadoop NameNode. S
Cassandra at Scale: The Problem with Secondary Indexes | Pantheon.io
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Cassandra Data Modeling Best Practices, Part 1
This is the first in a series of posts on Cassandra data modeling, implementation, operations, and related practices that guide our Cassandra utilization at eBay. Some of these best practices we’ve learned from public forums, many are new to us, and a few still are arguable and could benefit from further experience. September 2014 Update: Readers should note that this article describes data modeli
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Data Locality w/ Cassandra : How to Scan the Local Token Range of a Table...
Initializing a multiple node cluster (multiple data centers)
Ippon | Cabinet de conseil et expertise en technologie
About Indexes in Cassandra — Apache Cassandra 1.1.x documentation
Understanding the architecture
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