From d5a647a4abf2dda5b34fce3fe2ba5b76d090866f Mon Sep 17 00:00:00 2001 From: josh-wong Date: Thu, 16 Jan 2025 05:36:55 +0000 Subject: [PATCH] AUTO: Sync ScalarDB docs in English to docs site repo --- docs/glossary.mdx | 119 ++++++++++++++++++++++++++++ docs/scalardb-benchmarks/README.mdx | 4 +- 2 files changed, 121 insertions(+), 2 deletions(-) create mode 100644 docs/glossary.mdx diff --git a/docs/glossary.mdx b/docs/glossary.mdx new file mode 100644 index 00000000..6cd569d6 --- /dev/null +++ b/docs/glossary.mdx @@ -0,0 +1,119 @@ +--- +tags: + - Community + - Enterprise Standard + - Enterprise Premium +displayed_sidebar: docsEnglish +--- + +# Glossary + +This glossary includes database and distributed-system terms that are often used when using ScalarDB. + +## ACID + +Atomicity, consistency, isolation, and durability (ACID) is a set of properties that ensure database transactions are processed reliably, maintaining integrity even in cases of errors or system failures. + +## concurrency control + +Concurrency control in databases ensures that multiple transactions can occur simultaneously without causing data inconsistency, usually through mechanisms like locking or timestamp ordering. + +## consensus + +Consensus in distributed systems refers to the process of achieving agreement among multiple computers or nodes on a single data value or system state. + +## data federation + +Data federation is the process of integrating data from different sources without moving the data, creating a unified view for querying and analysis. + +## data mesh + +A data mesh is a decentralized data architecture that enables each business domain within a company to autonomously manage data and use it efficiently. + +## data virtualization + +Data virtualization is similar to data federation in many aspects, meaning that it virtualizes multiple data sources into a unified view, simplifying queries without moving the data. + +## database anomalies + +Database anomalies are inconsistencies or errors in data that can occur when operations such as insertions, updates, or deletions are performed without proper transaction management. + +## federation engine + +A federation engine facilitates data integration and querying across multiple disparate data sources, often as part of a data federation architecture. + +## global transaction + +A global transaction spans multiple databases or distributed systems and ensures that all involved systems commit or roll back changes as a single unit. + +## heterogeneous databases + +Heterogeneous databases refer to systems composed of different database technologies that may have distinct data models, query languages, and transaction mechanisms. + +## HTAP + +Hybrid transactional/analytical processing (HTAP) refers to a system that can handle both transactional and analytical workloads concurrently on the same data set, removing the need for separate databases. + +## JDBC + +Java Database Connectivity (JDBC) is an API that allows Java applications to interact with databases, providing methods for querying and updating data in relational databases. + +## linearizability + +Linearizability is a strong consistency model in distributed systems where operations appear to occur atomically in some order, and each operation takes effect between its start and end. + +## NoSQL database + +A NoSQL database is a non-relational databases designed for specific data models, such as document, key-value, wide-column, or graph stores, often used for handling large-scale, distributed data. + +## Paxos + +Paxos is a family of protocols used in distributed systems to achieve consensus, even in the presence of node failures. + +## PITR + +Point-in-time recovery (PITR) allows a database to be restored to a previous state at any specific time, usually after an unintended event like data corruption. + +## polystores + +Polystores are database architectures that allow users to interact with multiple, heterogeneous data stores, each optimized for a specific workload or data type, as if they were a single system. + +## read-committed isolation + +Read-committed isolation is an isolation level where each transaction sees only committed data, preventing dirty reads but allowing non-repeatable reads. + +## relational database + +A relational database stores data in tables with rows and columns, using a structured query language (SQL) to define, query, and manipulate the data. + +## replication + +Replication in databases involves copying and distributing data across multiple machines or locations to ensure reliability, availability, and fault tolerance. + +## Saga + +The Saga pattern is a method for managing long-running transactions in a distributed system, where each operation in the transaction is followed by a compensating action in case of failure. + +## serializable isolation + +Serializable isolation (serializability) is the highest isolation level in transactional systems, ensuring that the outcome of concurrently executed transactions is the same as if they were executed sequentially. + +## snapshot isolation + +Snapshot isolation is an isolation level that allows transactions to read a consistent snapshot of the database, protecting them from seeing changes made by other transactions until they complete. + +## TCC + +Try-Confirm/Cancel (TCC) is a pattern for distributed transactions that splits an operation into three steps, allowing for coordination and recovery across multiple systems. + +## transaction + +A transaction in databases is a sequence of operations treated as a single logical unit of work, ensuring consistency and integrity, typically conforming to ACID properties. + +## transaction manager + +A transaction manager coordinates the execution of transactions across multiple systems or databases, ensuring that all steps of the transaction succeed or fail as a unit. + +## two-phase commit + +Two-phase commit is a protocol for ensuring all participants in a distributed transaction either commit or roll back the transaction, ensuring consistency across systems. diff --git a/docs/scalardb-benchmarks/README.mdx b/docs/scalardb-benchmarks/README.mdx index bbb83980..58ac6bd9 100644 --- a/docs/scalardb-benchmarks/README.mdx +++ b/docs/scalardb-benchmarks/README.mdx @@ -97,9 +97,9 @@ After applying the schema and configuring the properties file, select a benchmar ### Prepare a benchmarking configuration file -To run a benchmark, you must first prepare a benchmarking configuration file. The configuration file requires at least the locations of the workload modules to run and the database configuration. +To run a benchmark, you must first prepare a benchmarking configuration file. The configuration file requires at least the locations of the workload modules to run and the database configuration. -The following is an example configuration for running the TPC-C benchmark. The ScalarDB properties file specified for `config_file` should be the properties file for the [benchmarking environment that you previously set up](#set-up-your-environment). +The following is an example configuration for running the TPC-C benchmark. The ScalarDB properties file specified for `config_file` should be the properties file that you created as one of the steps in [Load the schema](#load-the-schema). :::note