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AUTO: Sync ScalarDB docs in English to docs site repo (#837)
Co-authored-by: josh-wong <[email protected]>
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docs/glossary.mdx

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---
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tags:
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- Community
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- Enterprise Standard
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- Enterprise Premium
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displayed_sidebar: docsEnglish
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---
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# Glossary
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This glossary includes database and distributed-system terms that are often used when using ScalarDB.
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## ACID
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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.
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## concurrency control
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Concurrency control in databases ensures that multiple transactions can occur simultaneously without causing data inconsistency, usually through mechanisms like locking or timestamp ordering.
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## consensus
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Consensus in distributed systems refers to the process of achieving agreement among multiple computers or nodes on a single data value or system state.
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## data federation
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Data federation is the process of integrating data from different sources without moving the data, creating a unified view for querying and analysis.
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## data mesh
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A data mesh is a decentralized data architecture that enables each business domain within a company to autonomously manage data and use it efficiently.
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## data virtualization
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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.
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## database anomalies
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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.
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## federation engine
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A federation engine facilitates data integration and querying across multiple disparate data sources, often as part of a data federation architecture.
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## global transaction
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A global transaction spans multiple databases or distributed systems and ensures that all involved systems commit or roll back changes as a single unit.
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## heterogeneous databases
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Heterogeneous databases refer to systems composed of different database technologies that may have distinct data models, query languages, and transaction mechanisms.
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## HTAP
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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.
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## JDBC
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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.
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## linearizability
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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.
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## NoSQL database
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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.
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## Paxos
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Paxos is a family of protocols used in distributed systems to achieve consensus, even in the presence of node failures.
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## PITR
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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.
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## polystores
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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.
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## read-committed isolation
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Read-committed isolation is an isolation level where each transaction sees only committed data, preventing dirty reads but allowing non-repeatable reads.
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## relational database
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A relational database stores data in tables with rows and columns, using a structured query language (SQL) to define, query, and manipulate the data.
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## replication
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Replication in databases involves copying and distributing data across multiple machines or locations to ensure reliability, availability, and fault tolerance.
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## Saga
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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.
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## serializable isolation
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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.
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## snapshot isolation
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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.
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## TCC
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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.
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## transaction
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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.
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## transaction manager
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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.
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## two-phase commit
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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.

docs/scalardb-benchmarks/README.mdx

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### Prepare a benchmarking configuration file
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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.
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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.
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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).
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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).
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:::note
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