|
PACELC Theorem
In database theory, the PACELC design principle is an extension to the CAP theorem. It states that in case of network partitioning (P) in a distributed computer system, one has to choose between availability (A) and consistency (C) (as per the CAP theorem), but else (E), even when the system is running normally in the absence of partitions, one has to choose between latency (L) and loss of consistency (C). Overview The CAP theorem can be phrased as "PAC", the impossibility theorem that no distributed data store can be both consistent and available in executions that contains partitions. This can be proved by examining latency: if a system ensures consistency, then operation latencies grow with message delays, and hence operations cannot terminate eventually if the network is partitioned, i.e. the system cannot ensure availability. In the absence of partitions, both consistency and availability can be satisfied. PACELC therefore goes further and examines how the system replicates ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cosmos DB
Azure Cosmos DB is a globally distributed, multi-model database service offered by Microsoft. It is designed to provide high availability, scalability, and low-latency access to data for modern applications. Unlike traditional relational databases, Cosmos DB is a NoSQL (meaning "Not only SQL", rather than "zero SQL") and vector database, which means it can handle unstructured, semi-structured, structured, and vector data types. Data model Internally, Cosmos DB stores "items" in "containers", with these two concepts being surfaced differently depending on the API used (these would be "documents" in "collections" when using the MongoDB-compatible API, for example). Containers are grouped in "databases", which are analogous to namespaces above containers. Containers are schema-agnostic, which means that no schema is enforced when adding items. By default, every field in each item is automatically indexed, generally providing good performance without tuning to specific query patte ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Trilemma
A trilemma is a difficult choice from three options, each of which is (or appears) unacceptable or unfavourable. There are two logically equivalent ways in which to express a trilemma: it can be expressed as a choice among three unfavourable options, one of which must be chosen, or as a choice among three favourable options, only two of which are possible at the same time. The term derives from the much older term ''dilemma'', a choice between two or more difficult or unfavourable alternatives. The earliest recorded use of the term was by the British preacher Philip Henry in 1672, and later, apparently independently, by the preacher Isaac Watts in 1725. In religion Epicurus' trilemma One of the earliest uses of the trilemma formulation is that of the Greek philosopher Epicurus, rejecting the idea of an omnipotent and omnibenevolent God (as summarised by David Hume): # If God is unable to prevent evil, then he is not all-powerful. # If God is not willing to prevent evil, the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Raft (algorithm)
Raft is a consensus algorithm designed as an alternative to the Paxos family of algorithms. It was meant to be more understandable than Paxos by means of separation of logic, but it is also formally proven safe and offers some additional features. Raft offers a generic way to distribute a state machine across a cluster of computing systems, ensuring that each node in the cluster agrees upon the same series of state transitions. It has a number of open-source reference implementations, with full-specification implementations in Go, C++, Java, and Scala. It is named after Reliable, Replicated, Redundant, And Fault-Tolerant. Raft is not a Byzantine fault tolerant (BFT) algorithm; the nodes trust the elected leader. Basics Raft achieves consensus via an elected leader. A server in a raft cluster is either a ''leader'' or a ''follower'', and can be a ''candidate'' in the precise case of an election (leader unavailable). The leader is responsible for log replication to the f ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Project Management Triangle
The project management triangle (called also the ''triple constraint'', ''iron triangle'' and ''project triangle'') is a model of the constraints of project management. While its origins are unclear, it has been used since at least the 1950s. It contends that: # The quality of work is constrained by the project's budget, deadlines and scope (features). # The project manager can trade between constraints. # Changes in one constraint necessitate changes in others to compensate or quality will suffer. For example, a project can be completed faster by increasing budget or cutting scope. Similarly, increasing scope may require equivalent increases in budget and schedule. Cutting budget without adjusting schedule or scope will lead to lower quality. "Good, fast, cheap. Choose two." as stated in the Common Law of Business Balance (often expressed as "You get what you pay for.") which is attributed to John Ruskin but without any evidence and similar statements are often used to encapsula ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Paxos (computer Science)
Paxos is a family of protocols for solving consensus in a network of unreliable or fallible processors. Consensus is the process of agreeing on one result among a group of participants. This problem becomes difficult when the participants or their communications may experience failures. Consensus protocols are the basis for the state machine replication approach to distributed computing, as suggested by Leslie Lamport and surveyed by Fred Schneider. State machine replication is a technique for converting an algorithm into a fault-tolerant, distributed implementation. Ad-hoc techniques may leave important cases of failures unresolved. The principled approach proposed by Lamport et al. ensures all cases are handled safely. The Paxos protocol was first submitted in 1989 and named after a fictional legislative consensus system used on the Paxos island in Greece, where Lamport wrote that the parliament had to function "even though legislators continually wandered in and out of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lambda Architecture
Lambda architecture is a data processing, data-processing architecture designed to handle massive quantities of data by taking advantage of both batch processing, batch and stream processing, stream-processing methods. This approach to architecture attempts to balance latency (engineering), latency, throughput, and fault-tolerance by using batch processing to provide comprehensive and accurate views of batch data, while simultaneously using real-time stream processing to provide views of online data. The two view outputs may be joined before presentation. The rise of lambda architecture is correlated with the growth of big data, real-time analytics, and the drive to mitigate the latencies of map-reduce. Lambda architecture depends on a data model with an append-only, immutable data source that serves as a system of record.Bijnens, Nathan"A real-time architecture using Hadoop and Storm" 11 December 2013. It is intended for ingesting and processing timestamped events that are appende ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fallacies Of Distributed Computing
The fallacies of distributed computing are a set of assertions made by L Peter Deutsch and others at Sun Microsystems describing false assumptions that programmers new to distributed applications invariably make. The fallacies The originally listed fallacies are # The network is reliable; # Latency is zero; # Bandwidth is infinite; # The network is secure; # Topology doesn't change; # There is one administrator; # Transport cost is zero; # The network is homogeneous; The effects of the fallacies # Software applications are written with little error-handling on networking errors. During a network outage, such applications may stall or infinitely wait for an answer packet, permanently consuming memory or other resources. When the failed network becomes available, those applications may also fail to retry any stalled operations or require a (manual) restart. # Ignorance of network latency, and of the packet loss it can cause, induces application- and transport-layer developer ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Consistency Model
In computer science, a consistency model specifies a contract between the programmer and a system, wherein the system guarantees that if the programmer follows the rules for operations on memory, memory will be data consistency, consistent and the results of reading, writing, or updating memory will be predictable. Consistency models are used in Distributed computing, distributed systems like distributed shared memory systems or distributed data stores (such as filesystems, databases, optimistic replication systems or web caching). Consistency is different from coherence, which occurs in systems that are cache coherence, cached or cache-less, and is consistency of data with respect to all processors. Coherence deals with maintaining a global order in which writes to a single location or single variable are seen by all processors. Consistency deals with the ordering of operations to multiple locations with respect to all processors. High level languages, such as C++ and Java (progr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
MongoDB
MongoDB is a source-available, cross-platform, document-oriented database program. Classified as a NoSQL database product, MongoDB uses JSON-like documents with optional database schema, schemas. Released in February 2009 by 10gen (now MongoDB Inc.), it supports features like sharding, Replication (computing), replication, and ACID transactions (from version 4.0). MongoDB Atlas, its managed cloud service, operates on AWS, Google Cloud Platform, and Microsoft Azure. Current versions are licensed under the Server Side Public License (SSPL). MongoDB is a member of the MACH Alliance. History The American software company 10gen began developing MongoDB in 2007 as a component of a planned platform as a service, platform-as-a-service product. In 2009, the company shifted to an open-source development model and began offering commercial support and other services. In 2013, 10gen changed its name to MongoDB Inc. On October 20, 2017, MongoDB became a publicly traded company, listed on N ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache HBase
HBase is an open-source non-relational distributed database modeled after Google's Bigtable and written in Java. It is developed as part of Apache Software Foundation's Apache Hadoop project and runs on top of HDFS (Hadoop Distributed File System) or Alluxio, providing Bigtable-like capabilities for Hadoop. That is, it provides a fault-tolerant way of storing large quantities of sparse data (small amounts of information caught within a large collection of empty or unimportant data, such as finding the 50 largest items in a group of 2 billion records, or finding the non-zero items representing less than 0.1% of a huge collection). HBase features compression, in-memory operation, and Bloom filters on a per-column basis as outlined in the original Bigtable paper. Tables in HBase can serve as the input and output for MapReduce jobs run in Hadoop, and may be accessed through the Java API but also through REST, Avro or Thrift gateway APIs. HBase is a wide-column store a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bigtable
Bigtable is a fully managed wide-column and key-value NoSQL database service for large analytical and operational workloads as part of the Google Cloud portfolio. History Bigtable development began in 2004.. It is now used by a number of Google applications, such as Google Analytics, web indexing, MapReduce, which is often used for generating and modifying data stored in Bigtable, Google Maps,. Google Books search, "My Search History", Google Earth, Blogger.com, Google Code hosting, YouTube, and Gmail. Google's reasons for developing its own database include scalability and better control of performance characteristics. Apache HBase and Cassandra are some of the best known open source projects that were modeled after Bigtable. Bigtable offerHBaseanCassandra compatible APIs On May 6, 2015, a public version of Bigtable was made available as a part of Google Cloud under the name Cloud Bigtable. As of April 2024, Bigtable manages over 10 Exabytes of data and serves more ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
